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COLLEGE ALGEBRA COURSE OUTCOMES AMONG NONTRADITIONAL COMMUNITY COLLEGE STUDENTS A Dissertation by JEANETTA D. GROCE Submitted to the Office of Graduate Studies of Texas A&M UniversityCommerce in partial fulfillment of the requirements for the degree of DOCTOR OF EDUCATION August 2015 COLLEGE ALGEBRA COURSE OUTCOMES AMONG NONTRADITIONAL COMMUNITY COLLEGE STUDENTS A Dissertation by JEANETTA D. GROCE Approved by: Advisor: Joyce A. Scott Committee: Jon Travis Mark Reid Head of Department: William C. Holt Dean of the College: Timothy Letzring Dean of Graduate Studies: Arlene Horne iii Copyright © 2015 Jeanetta D. Groce iv ABSTRACT COLLEGE ALGEBRA COURSE OUTCOMES AMONG NONTRADITIONAL COMMUNITY COLLEGE STUDENTS Jeanetta D. Groce, EdD Texas A&M UniversityCommerce, 2015 Advisor: Joyce A. Scott, PhD An increasing number of nontraditional students are enrolling in community colleges to achieve their educational and career goals. For many of these students, degree completion is contingent upon the successful completion of college algebra, a course that nearly 50% of enrolled students fail to complete successfully. Nontraditional students, who are more likely to be balancing school, work, and family responsibilities, are often enrolled part time and often rely on the flexibility of online classes. These students are also more likely to be referred to developmental mathematics prior to enrolling in college algebra. The purposes of this study were (a) to examine college algebra course outcomes among adult community college students to determine if differences exist between those who take the class live and those who take it online, (b) to determine if differences exist in college algebra course outcomes based on previous enrollment in developmental mathematics and, (c) to determine if differences exist in college algebra course outcomes based on parttime/fulltime status. v The study participants were community college algebra students age 25 and older. Volunteer participants were recruited from online and live college algebra students enrolled at a large rural community college in North Texas. Informed consent and relevant demographic data were collected through the use of a categorical response questionnaire administered during a 3week period immediately following the midterm exam. Final course grades were provided by the cooperating community college’s mathematics department chairperson at the conclusion of the semester. A chisquare test of independence was used to analyze the data. No statistically significant relationships were identified between college course outcomes and course delivery format, previous enrollment in developmental mathematics, or enrollment status. Findings indicated, however, that a higher percentage of students were successful in the live sections than in the online sections. In addition, participants who had never been enrolled in developmental mathematics passed college algebra at a higher rate than those who had been enrolled in developmental mathematics. Finally, although no statistically significant relationship existed between course outcomes and parttime or fulltime enrollment status, it was noted that parttime students were more likely to enroll in online sections than in live sections. vi ACKNOWLEDGEMENTS First and foremost, I give honor and praise to my Lord and Savior Jesus Christ who has not only saved me, but also carried, strengthened, and blessed me throughout my life. As with other trials in my life, the journey toward the completion of my doctorate has reminded me that, “The LORD is my strength and my defense; He has become my salvation. He is my God, and I will praise him…” (Exodus 15:2). I dedicate this dissertation to Dr. Brenda Reed, who first taught me, at the age of 31, that I was not “math stupid” and that I could, indeed, do math, even algebra. Without you, Dr. Shari Beck, and Dr. Vanessa Huse, none of this would have been possible. I owe a tremendous debt of gratitude to my advisor, Dr. Joyce Scott. Thank you for taking me on halfway through the program and for restoring my faith in the process. Thank you for your continuous support, for your wisdom, and for the hours and hours of editing you did for me. You have been amazing. To Dr. Jon Travis, thank you for making us work so hard in the law class, for doing an independent study so I could stay on track, for agreeing to serve on my committee, and for holding up the standards of the “old guard.” I appreciate that more than you know. To Dr. Katy Denson, I am absolutely certain that God sent you my way when I needed assistance with the statistical processes of this study. I will be eternally grateful for your expertise and your willingness to help. I could not have done this without you. To Dr. Mark Reid, thank you for stepping onto my committee on such short notice and so late in the process. I definitely owe you one. Finally, to my family and friends, thank you, thank you, thank you! You have supported me beyond reason, listened to me complain, encouraged me, and picked up the slack when I was too swamped to do my part. How could I ask for more? vii TABLE OF CONTENTS LIST OF TABLES ...........................................................................................................................x CHAPTER 1. INTRODUCTION ........................................................................................................ 1 Statement of the Problem ....................................................................................... 7 Purpose of the Study .............................................................................................. 7 Research Questions ................................................................................................ 8 Hypotheses ............................................................................................................. 8 Significance of the Study ....................................................................................... 9 Method of Procedure............................................................................................ 16 Institution Board Approval ...................................................................... 16 Design of Study........................................................................................ 17 Selection and Development of Instruments ............................................. 18 Selection of Sample ................................................................................. 18 Collection of Data .................................................................................... 19 Treatment of the Data .............................................................................. 20 Definitions of Terms ..............................................................................................20 Limitations .............................................................................................................23 Delimitations ..........................................................................................................23 Assumptions ...........................................................................................................24 Organization of Dissertation Chapters ...................................................................24 viii CHAPTER 2. REVIEW OF THE LITERATURE ...............................................................................25 Nontraditional Students .........................................................................................25 Developmental Education ......................................................................................35 College Algebra .....................................................................................................47 Online Classes ........................................................................................................54 Conclusion .............................................................................................................64 3. METHOD OF PROCEDURE........................................................................................65 Research Questions ................................................................................................65 Hypotheses .............................................................................................................66 Design of Study......................................................................................................66 Description of Instruments .....................................................................................68 Collection of Data ..................................................................................................69 Treatment of Data ..................................................................................................70 Summary ................................................................................................................73 4. PRESENTATION OF FINDINGS ................................................................................74 Research Questions ................................................................................................74 Hypotheses .............................................................................................................75 Data Collection ......................................................................................................75 Results ....................................................................................................................76 Summary ................................................................................................................82 ix CHAPTER 5. SUMMARY OF FINDINGS, IMPLICATIONS, CONCLUSIONS, AND RECOMMENDAIONS FOR FUTURE RESEARCH..................................................83 Summary of the Study ...........................................................................................84 Findings..................................................................................................................85 Conclusions ............................................................................................................89 Implications............................................................................................................90 Recommendations for Future Research .................................................................91 Summary ................................................................................................................91 REFERENCES ............................................................................................................................ 93 APENDICES...............................................................................................................................106 Appendix A. Student Invitation Email ...................................................................................107 B. Student Invitation ..............................................................................................109 C. Informed Consent Form ....................................................................................111 D. Questionnaire ....................................................................................................114 VITA ...........................................................................................................................................116 x LIST OF TABLES TABLE 1. Cross Tabulation of Course Outcome and Course Type ....................................................77 2. Cross Tabulation of Course Outcome and Developmental Mathematics Status ................79 3. Cross Tabulation of Course Type and Developmental Mathematics Status ......................80 4. Cross Tabulation of Course Type and Enrollment Status ..................................................82 1 Chapter 1 INTRODUCTION According to the Organisation for Economic Cooperation and Development (OECD), “Governments are increasingly looking to international comparisons of education opportunities and outcomes as they develop policies to enhance individuals’ social and economic prospects, provide incentives for greater efficiency in schooling, and help to mobilise resources to meet rising demands” (2014, p. 3). Higher levels of educational attainment have been associated with benefits for both individuals and societies around the world. Completing a tertiary program, typically referred to in the United States as a 2year, 4year, or graduate program, has been associated with better health, increased career opportunities, and higher earnings for individuals. Consequently, societies benefit from higher proportions of tertiaryeducated citizens through higher employment rates, reduced welfare expenditures, and increased tax revenue. Considering lost income and public grants, the public recovers four times the cost associated with providing a man with a tertiary education and two and a half times the cost of educating a woman to the same level (OECD, 2014). In OECD countries, employment rates remained consistently higher among tertiaryeducated adults from 20072012. In 2012, 80% of OECD tertiaryeducated adults between the ages of 25 and 64, compared to 70% of adults with a secondary credential, were employed. Older tertiaryeducated adults were slightly more likely to be employed than were younger adults with the same level of education. (OECD, 2014). The OECD associated greater educational achievement with increased lifetime income but found a particularly large increase among the more educated older adults. The organization maintained that, “People with higher levels of 2 education are more likely to be employed, and remain employed, and have more opportunities to gain experience on the job” (OECD, 2014, p. 134). The percentages of tertiaryeducated adults increased by 10% across all OECD countries between 2000 and 2012, with approximately 34% of women and 31% of men completing a college degree (OECD, 2014). Much of the growth has been attributed to an increase in the number of younger adults who completed degrees, but the average age at which students earned a university degree varied in 2012. Across all OECD countries, students completed a university degree at approximately 27 years of age. In Belgium, Luxemburg, Mexico, the Netherlands, and the United Kingdom, students earned the degree approximately 2 years earlier, at 25 years of age. Students in Brazil, Finland, Sweden, Iceland, and Israel tended to complete a university degree at the older age of 29 (OECD, 2014). The percentage of parttime students also varied. Of tertiary students in all OECD countries, 21% were enrolled part time in 2012. In Argentina, Finland, Hungary, New Zealand, the Slovak Republic, Spain, and the United States, the percentage of parttime students was 30%, significantly higher than the global average (OECD, 2014). Approximately 10% of adults in OECD countries participated in some formal education in 2012. The percentages were above average in AngloSaxon countries (including the United States), Nordic countries, the Netherlands, and Spain. In contrast, France, Japan, and Korea had below average adult enrollment with less than 5% of adults participating in formal education (OECD, 2014, p. 396). According to the OECD (2014), the proportion of adults in education programs may be reflective of the flexibility required by older students. Across all OECD countries, 45% of adults who indicated a desire, but inability, to participate in learning activities during the preceding year, specified work and family responsibilities as the reason why they 3 were unable to participate. An additional 14% asserted that cost was a factor, 12% indicated that the desired program was not available at a convenient time or location, 8% referred to a “lack of employer support,” 4% indicated that unexpected events or circumstances prevented them from attending, and 3% stated that they did not have the prerequisites (OECD, 2014, p. 395). Governments around the world have introduced programs to encourage degree completion among older adults who may be unable to earn a credential in the expected timeframe due to the need to balance work and study requirements (OECD, 2014). Although extending the time to completion increases the cost of adult degree acquisition, adults may be more certain of their chosen major and may be more motivated to complete the degree. As stated by the OECD, It is crucial to provide, and ensure access to, organised learning opportunities for adults beyond their initial formal education, especially for workers who need to adapt to changes throughout their careers. The relevance of continued learning opportunities now extends to workers in both high and lowskilled occupations. (2014, p. 390) Information supplied by the U.S. Census Bureau and the U.S. Department of Labor (see below) supported the need to ensure access to higher education among nontraditional students in the United States, as well. According to the U.S. Census Bureau, American FactFinder (2013), over 52% of Americans were between the ages of 25 and 64 in 2013, and the median age of the total population was 37.5 years. Only 10% of the American population was between the ages 18 and 24, the ages typically associated with college attendance, yet 31.1% of American females and 25.4% of American males age three and older were enrolled in college or graduate school in 2013. In the same year, nearly 60% of Americans age 16 and over were employed (U.S. Census 4 Bureau, American FactFinder, 2013). These numbers suggest significant college enrollment among working American adults over the age of 24. In the United States, college enrollment increased by 32% between 2001 and 2011 (Snyder & Dillow, 2013). Enrollment increases were not equal across age groups, however. During this time, enrollment among students under 25 increased by 35%, while enrollment among students 25 or older increased by 41%. Although the difference in enrollment increases between the two age groups is expected to narrow between 2011 and 2021, enrollment among older students is expected to remain slightly higher than that of younger students (Snyder & Dillow, 2013). The average time to degree completion varies widely in the United States. In 2008, the median time in which students completed a bachelor’s degree was 52 months (Cataldi et al., 2011). During that year, 44% of all graduates completed a bachelor’s degree in 48 months, 23% completed in 4960 months, and 9% completed the degree in 6172 months. Students who began their postsecondary education at 4year institutions graduated in less time than students who began at 2year institutions. Students who first attended 4year institutions earned a bachelor’s degree in approximately 47 months, compared to 63 months for those who first attended 2year institutions. A significant difference in completion times was also found between students who attended college immediately after high school and those who did not. Students who started college within one year of high school graduation earned a bachelor’s degree in about 51 months, compared to approximately 80 months for those who delayed enrollment (Cataldi et al., 2011). In 2014, U.S. Department of Labor, Bureau of Labor Statistics (BLS) found that educational attainment was associated with higher employment rates for American adults 25 and older. In 20102011, 22% of U.S. workers 25 and older had some college, but no degree. An 5 additional 9% had an associate’s degree, and 21.6% had a bachelor’s degree as the highest level of educational attainment. In 2013, unemployment rates were 7.5% for those with only a high school diploma; 7.0% for those with some college, but no degree; 5.4% for those with an associate’s degree, and 4.0% for those with a bachelor’s degree. People with bachelor’s degrees were also found to be less affected by rising unemployment rates between 2008 and 2010 than were those without bachelor’s degrees (Kena et al., 2014). The U.S. Department of Labor, BLS, found that, “Occupations that typically require postsecondary education for entry have higher wages” (2013a, p. 6). Among adults who were at least 25 years old and employed fulltime in 2013, the average weekly income was $651 a week for those with only a high school diploma; $727 for those with some college, but no degree; $777 for those with an associate’s degree; and $1,108 for those with a bachelor’s degree (U.S. Department of Labor, BLS, 2014). According to the data, adults with bachelor’s degrees earned an average of $457 per week more than those with only a high school diploma and $381 per week more than adults who began college but did not earn a degree. This difference in average earned income is especially relevant when one considers that 15.8% of all Americans and 22.2% of American children lived in poverty in 2013 (U.S. Census Bureau, American FactFinder, 2013). In 2012, approximately onethird of all U.S. entrylevel jobs required at least some postsecondary education (U.S. Department of Labor, BLS, 2013a). Between 2012 and 2022, some 108,882,000 new and replacement jobs are expected to require either an associate’s or bachelor’s degree (U.S. Department of Labor, BLS, 2013b). In 2013, however, slightly less than 30% of American adults 25 and older had some college or an associate’s degree, and only 18.4% had a bachelor’s degree (U.S. Census Bureau, American FactFinder, 2013). 6 While the data support the financial benefits of completing a college degree, adult students have complex lives and varied reasons for enrolling in college. Adults may enroll or reenroll in college to create additional career opportunities, create a better life, or grow intellectually. Kasworm (2008) noted, however, that when adults assume the role of student, the new responsibility does not replace or diminish existing obligations, but is added to them. The challenges and complexities associated with balancing these roles and creating more opportunities may simultaneously bolster and challenge adult students’ sense of self. Kasworm also stated that adult students “believe they have a high probability of success and are committed to quality learning experiences and a collegiate credential” (2008, p. 28). “While adult students are often more motivated and more determined to overcome their unique obstacles than traditionalage students, mathematics courses prove to be barriers to adult student graduation” (Tennant, 2014, p. 17). Students 25 and older typically scored significantly lower on math placement tests than traditional students and were more likely to be placed into developmental mathematics classes (Calcagno, Crosta, Bailey, & Jenkins, 2007b; Tennant, 2014). Studies examining the effects of developmental mathematics on nontraditional student completion rates have produced mixed results. Being underprepared for collegelevel mathematics has been identified as a significant dropout risk factor for all students (Tennant, 2014). However, Calcagno et al. (2007a, 2007b) found that, when controlling for math ability, nontraditional students were more likely to graduate than their younger counterparts. Tennant (2014), however, found that, although nontraditional students who were prepared for collegelevel mathematics had graduation rates similar to younger students who were prepared for collegelevel math, the rates were dissimilar among those students who were not prepared. According to Tennant (2014), nontraditional students who began in developmental mathematics 7 classes were less likely or much less likely to graduate than were younger students who began in developmental mathematics classes. Statement of the Problem High failure rates in college algebra may prove to be a barrier to degree completion for adult students who may have had little exposure to formal mathematics instruction for an extended period of time (Hardin, 2008; Thiel, Peterman, & Brown, 2008). Developmental education, which accounted for $206 million of the 20062007 Texas biennial budget (Pretlow & Wathington, 2012), may actually serve as an additional barrier rather than as a benefit for college completion (Charles A. Dana Center, Complete College America, Inc., Education Commission of the States, & Jobs for the Future, 2012). The problem may be compounded by a change in course delivery modes as more nontraditional students enroll in online classes. The goal of this study was to explore the possible relationship between course delivery format, previous enrollment in developmental mathematics, and college algebra course outcomes for adult students. Purpose of the Study The primary purpose of this study was to examine college algebra course outcomes among adult community college students to determine if differences exist between those enrolled in live and online college algebra classes. Additional purposes were to determine if differences exist in college algebra course outcomes based on previous enrollment in developmental mathematics and parttime/fulltime status. 8 Research Questions The following research questions guided the study: 1. Does a statistically significant relationship exist between college algebra course outcomes and online or live enrollment among adult community college students? 2. Does a statistically significant relationship exist between college algebra course outcomes and previous enrollment in developmental mathematics among adult community college students? 3. Does a statistically significant relationship exist between college algebra course outcomes and course type (online or live) with previous enrollment in developmental mathematics among adult community college students? 4. Does a statistically significant relationship exist between college algebra course outcomes and course type (online or live) with enrollment status (parttime or fulltime) among adult community college students? Hypotheses The following null hypotheses were tested at the .05 level of significance: 1. No significant relationship exists between college algebra course outcomes and online or live enrollment among adult community college students. 2. No significant relationship exists between college algebra course outcomes and previous enrollment in developmental mathematics among adult community college students. 3. No significant relationship exists between college algebra course outcomes and course type (online or live) with previous enrollment in developmental mathematics among adult community college students. 9 4. No significant relationship exists between college algebra course outcomes and course type (online or live) with enrollment status (parttime or fulltime) among adult community college students. Significance of the Study Postsecondary education is a factor in employment trends. While national unemployment rates increased across all education levels between 2008 and 2010, and subsequently dropped between 2010 and 2013, unemployment levels remained lowest among people who held a bachelor’s degree or higher (Kena et al., 2014). Carnevale, Smith, and Strohl (2010) predicted a similar pattern for Texas. The number of new Texas jobs requiring at least some postsecondary education is expected to increase by 1.3 million between 2008 and 2018, with an estimated 56% of all Texas jobs projected to demand at least some college by 2018. Complete College America (2013) found that many students are not completing their degrees within expected timeframes, however. An analysis of the 20092010 graduation rates indicated that fewer than 30% of Texas college students graduated on time, within 2 years for an associate’s degree or within 4 years for a baccalaureate degree. On average, fulltime Texas students completed an associate’s degree in 4.7 years and a bachelor’s degree in 5.3 years. Parttime students completed an associate’s degree in an average of 5.2 years and a bachelor’s degree in an average of 6 years (Complete College America, 2013). In 2011, students 25 years of age and older accounted for 29% of the fulltime and 48% of the parttime enrollment at public 2year institutions in the United States (Kena et al., 2014). In the same year, 50% of all Texas college students were enrolled part time, and data indicated that less than 25% of parttime Texas students completed an associate’s degree within 6 years (Complete College America, 2013). In the fall of 2013, some 73% of all Texas community 10 college students were enrolled part time (THECB, 2014a). These growth trends are expected to continue. Kena et al. (2014) projected that enrollment in public 2year institutions will increase by 16% and parttime undergraduate enrollment will increase by 17% in the United States from 2012 to 2023. While college enrollment is expected to increase, attrition has continued to plague higher education. Between the 20042005 and 20082009 academic years, one fifth of all U.S. firsttime, fulltime community college students dropped out prior to their second year of college (Schneider & Yin, 2011). In the 20082009 academic year alone, American taxpayers spent $1 billion on firsttime fulltime college students who did not return for their second year. In the same year, Texas ranked second in the nation in the amount of expenditures for firstyear community college students who later withdrew before completing a program or degree. Between 2004 and 2009, Texas residents spent $360 million dollars in expenditures on firsttime community college students who quit prior to their second year of college (Schneider & Yin, 2011). In the fall of 2011, nearly 35% of the instate students enrolled in Texas public 2year institutions were at least 25 years of age. Factors such as a poor economy, global outsourcing, increasing technology, and a need for new job skills have contributed to increased enrollment among students 25 years of age and older, also referred to as nontraditional students (Jesnek, 2012). College enrollment among adults aged 50 and older has also increased as older adults have increasingly sought new employment opportunities beyond the traditional retirement age (Vacarr, 2014). If enrollment trends follow projected population patterns, the percentage of nontraditional students may continue to increase over time. The percentage of adults older than traditional 11 college age is expected to continue to rise in Texas and across the United States. By the year 2020, slightly over half of the Texas population is expected to be at least 35 years of age, representing a 2% increase over 2012 (THECB, 2013b). The U.S. Census Bureau (2010) projected that the number of adults aged 55 and older will increase by 36 million between 2014 and 2030. Vacarr (2014) summarized the growing population of older students and recognized the challenges they face by stating that: At a time when traditional “retirement” increasingly marks the beginning of a new phase of work (whether by choice, necessity, or some combination of the two), millions will need help if they are to make a successful transition. Looking toward another two, three, or even four decades of healthy active life, many people are eager to gain new skills and the credentials that will help them move into a new worklife chapter. Like students of traditional college age, they will also need help navigating what is fast being recognized as one of life’s major transitions, akin to adolescence in its significance. Here we have the makings of a winwin scenario. Colleges need students, and a growing underserved population needs supportive educational pathways into a new life chapter, precisely what colleges have historically provided. (p. A 52) Nontraditional students are more likely to attend college part time and often take longer to graduate than traditional students (Calcagno et al., 2007a; Newbold, Mehta, & Forbus, 2010; Tinto, 2012). Tinto (2012) noted that parttime students have many obligations and therefore go to campus only to attend class. Tinto further maintained that, for parttime students, college success depends on success in the classroom. 12 In addition to dealing with demands outside of the classroom, nontraditional students may “experience academic difficulties because they have been away from an academic setting for an extended time” (Hardin, 2008, p. 54). Adult learning is simultaneously physical, cognitive, and emotional; and adult students may experience anxiety, fear, and excitement upon returning to school (Willans & Seary, 2011). Further, nontraditional students are more likely than their younger counterparts to begin college lacking the computer proficiency necessary to succeed in most college courses (Jesnek, 2012). All of these factors may affect student success. McGrath (2009) asserted that andragogy “aims to look at how learning in the classroom can be made more attractive for adult students” (p. 109). Andragogy, a theory of adult learning founded primarily by Malcolm Knowles, developed over a period of 50 years and has been defined as “the art and science of helping adults learn” (Knowles, Holton, & Swanson, 2011, location 1155). Rooted in humanism and pragmatism, andragogy has been described as an “individualtransactional model of adult learning.” Unlike pedagogy, which is focused on covering specific content and organizing materials and lessons into manageable units, andragogy is focused on the learning process. Adult motivation continues to be an important factor in adult learning. Rodrigues asserted that, “Learners see education as a process for achieving their full potential in life” (2012, p. 31). Knowles et al. (2011) asserted that adults are primarily motivated by internal issues such as the desire for professional growth, a better quality of life, and higher selfesteem. Knowles et al. (2011) additionally noted that adults are motivated by personal goals, interest, and by clearly stated learning objectives. The Charles A. Dana Center et al. (2012) found that developmental instruction, intended to prepare students for entrylevel courses, may actually serve as a barrier to degree completion. 13 Despite the fact that 70% of all U.S. community college students enroll in at least one developmental course, 72% to 80% of those students fail to register for the subsequent entrylevel course (Bahr, 2010; Charles A. Dana Center et al., 2012; Templin, 2011; Wolfle, 2012). These numbers support findings that approximately 75% of community college students who enroll in developmental classes fail to earn a degree or to transfer to another institution within 8 years (Charles A. Dana Center et al., 2012; Parker, 2012). Bonham and Boylan (2012) stated that, “Developmental mathematics as a barrier to educational opportunity represents a serious concern for the students as well as higher education policy makers” (p. 14). Older students are significantly more likely than traditionally aged students to be assigned to the very beginning stages of the developmental mathematics sequence (Complete College America, 2012; Walker & Plata, 2000). This finding is concerning, as studies indicated a strong negative correlation between enrollment in the lower levels of developmental mathematics and subsequent success in college algebra (Doyen, 2012; Donovan & Wheland, 2008). While Fike and Fike found that “students successful in the developmental course ‘catch up’ with their collegeready peers” (2012, p. 8), only 13% of nontraditional community college freshmen who enroll in a developmental course ever complete the associated entrylevel course (Complete College America, 2012). College algebra, a requirement for most undergraduate degrees, may block degree completion. Every year, nearly half of the 1,000,000 U.S. college algebra students fail to pass the class (Herriott & Dunbar, 2009). Studies investigating a possible correlation between student age and success in college algebra have produced inconsistent results. Penny and White (1998) and Wolfle (2012) identified a weak positive correlation between student age and success in college algebra. On the other hand, studies investigating a relationship between student age, 14 previous enrollment in developmental mathematics, and success in college algebra produced different results. Doyen (2012) found that among students who had completed intermediate algebra within the previous calendar year, students 25 and older succeeded in college algebra at a slightly higher rate than did traditional students. Conversely, Calcagno et al. (2007b) found that nontraditional students who had taken developmental mathematics were less successful in college algebra than were traditional age students. In the United States, enrollment in online classes increased considerably faster than the overall student enrollment between 2002 and 2012. While the overall U.S. higher education enrollment grew at a rate of 2.5% annually, the annual compound growth rate of U.S. online enrollment reached 16.1% during this period. In the fall of 2012, online enrollment accounted for approximately one third of all enrollments in U.S. public degreegranting institutions (Allen & Seaman, 2014). Distance education, including online enrollment, has also grown in Texas. In fall 2000, distance education accounted for 15.3% of all attempted semester credit hours at Texas public community and technical colleges. By spring 2014 this percentage had increased to 35.4% (THECB, 2014b). Older students register for online classes at higher rates than younger students (Harris & Martin, 2012; Wilson & Allen, 2011). Although students 25 and older may actually prefer live classes, they often register for online classes due to accessibility and convenience (Beaghan, 2013). Students in Harris and Martin’s (2012) study identified flexibility in assignment completion, distance from campus, and the ability to attend school while still fulfilling family and jobrelated responsibilities as the primary factors motivating online enrollment. Once enrolled in online courses, motivation to continue is an important factor for adult students. Rodrigues (2012) found that nontraditional students were motivated to continue the 15 online learning process through continuous feedback and positive reinforcement. McGrath (2009) asserted that nontraditional students’ motivation to remain and participate in the online learning environment may also be increased through participation in collaborative small groups and increased perceptions of belonging. Online adult instructors in one study indicated a strong belief that participating in a carefully designed educational environment could be highly motivating to adult students if content learning occurred in a way that also improved selfesteem and encouraged a feeling of achievement (Wang & KaniaGosche, 2011). It is interesting to note that the ability to share both personal and academic experiences was found to be important to adult learners. Allen and Seaman (2014) reported that 45% of public U.S. higher education institutions found attrition to be a bigger problem in online than in faceface classes, however. This finding is consistent with Pontes and Pontes’ (2012) conclusion that distance education students were significantly more likely to drop out or to experience an enrollment gap than live students. Fetzner (2013) found that 47% of students who were unsuccessful in at least one online class attributed their failure to falling behind in class and not being able to complete all of the missed assignments, to dealing with personal problems such as child care and health concerns, and to being unable to balance school, work, and family responsibilities. Tinto (2012) stated, “In admitting a student, a college enters into a contract—indeed, takes a moral obligation—to establish those conditions on campus, especially in the classroom, that enhance the likelihood that students who are willing to expend the effort will succeed” (p. 120). Rodrigues (2012) noted that although many adults do not have a strong mathematical knowledge base, their commitment to attend and to participate in class indicates a readiness to learn. College algebra continues to serve as a roadblock to degree completion, especially for 16 nontraditional students who often enroll in college classes lacking the necessary technology and mathematics skills. Leaders in higher education need to take into account this deficit among nontraditional students and to conduct further research in two areas: to determine if a difference exists in course outcomes among nontraditional students enrolled in online versus live college algebra classes, and to ascertain if prior enrollment in developmental mathematics classes is a predictor of success or failure in either or both formats. The results of such research may allow colleges and universities to serve better the unique needs of nontraditional students, thus improving outcomes for students and institutions of higher education and preparing more graduates for the workforce of the future. Method of Procedure The purpose of this study was to examine the college algebra course outcomes among adult community college students. The assessment was accomplished by determining if any significant differences exist in course outcomes for students based on course type, previous enrollment in developmental mathematics, and fulltime or parttime enrollment status. The procedures used include the (a) Institutional Review Board Approval, (b) Design of the Study, (c) Selection and Development of Instruments, (d) Selection of Participants, (e) Collection of Data, and (f) Treatment of Data. Institutional Review Board Approval The researcher completed the Collaborative Institutional Training Initiative online Protection of Human Subjects Course, the Social and Behavioral Responsible Conduct of Research Course, and Conflict of Interest Course as a requirement to conduct research. Permission to conduct this study was granted by the Texas A&M UniversityCommerce Institutional Review Board (IRB). Permission to conduct this study at the participating 17 community college was received from the college’s Office of Institutional Research and Outreach. Design of the Study This study was ex post facto because the researcher was “unable to cause a variable to occur by creating a treatment and must examine the effects of a naturalistically occurring treatment after it has occurred” and because the researcher sought to “relate this afterthefact treatment to an outcome or dependent measure” (Tuckman & Harper, 2012, p. 172). This study followed a causalcomparative design as the researcher was “contrasting the characteristics of state with those of its opposite” (Tuckman & Harper, 2012, p. 182). This quantitative study used the chisquare test to determine if relationships existed between college algebra course outcome and several groups of nontraditional students. All variables were categorical, with two levels each. When categorical data are collected, the number or frequency that fall into each category are analyzed (Field, 2013). The dependent variable, course outcome, was categorical with two possible outcomes of pass or fail. Other categorical variables, thought of as the independent variables, were the type of class (live or online), previous enrollment in developmental mathematics (yes or no), and enrollment status (fulltime or parttime). A literature review revealed the significance of including the independent variables in the study (Allen & Seaman, 2014; Bahr, 2010; Calcagno et al, 2007a; Calcagno et al, 2007b; Charles A. Dana Center et al., 2012; Complete College America, 2013; Fetzner, 2013; Ghaffari, 2011; Parker, 2012; Pretlow & Wathington, 2012; Wolfle, 2012). A categorical response questionnaire solicited student age, type of class, previous enrollment in developmental mathematics, and enrollment status (Tuckman & Harper, 2012). The dependent variable was the course outcome of pass or fail. The literature revealed the significance of the dependent variables in the study (CarneyCrompton, & 18 Tan, 2002; Doyen, 2012; Penny & White, 1998; Pontes & Pontes, 2012). Final course outcomes were collected from the institution participating in the study at the conclusion of the semester. Selection and Development of Instruments The categorical response questionnaire used to collect data for the study was fashioned from an examination of the literature (Allen & Seaman, 2014; Bahr, 2010; Calcagno, Coast, Bailey, & Jenkins, 2007a; Calcagno, Coast, Bailey, & Jenkins, 2007b; Charles A. Dana Center et al., 2012; Complete College America, 2013; Fetzner, 2013; Ghaffari, 2011; Parker, 2012; Pretlow & Wathington, 2012; Wolfle, 2012). The questionnaire had four categorical response questions designed to gather data regarding student age, type of class (online or live), previous enrollment in developmental mathematics (yes or no), and enrollment status (fulltime or parttime). The questionnaire was reviewed for validity by the researcher’s advisor and an additional faculty member from the Department of Educational Leadership. The questionnaire was also reviewed by the mathematics department chairperson at the cooperating Texas community college. All suggested revisions were completed before the questionnaire was distributed to study participants. To establish reliability, the questionnaire was pilottested by a sample of community college algebra students. One area of weakness related to the renumbering of developmental mathematics classes was noted and corrected for clarity (Tuckman & Harper, 2012). Students who participated in the pilottesting were not included in the study sample. Selection of Sample Quantitative research allows for convenience sampling for the purpose of making generalizations about the target population (Creswell, 2005). For this quantitative study, the target population was community college students, aged 25 and older, who were enrolled in 19 online or live college algebra classes in spring 2015. A sample from the target population consisted of students 25 and older who were enrolled in online and live college algebra classes at four campuses of a large rural community college in North Texas. Students age 25 and older accounted for approximately 28% of the entire enrollment at the selected community college. Participation in the study was voluntary. All college algebra students, including those who were enrolled in an online class, were required to take a live midterm exam. Initial recruiting of potential participants occurred when they went to campus to take the midterm exam. The researcher then visited live sections of the course to recruit additional volunteer participants. An informed consent form and brief categorical response questionnaire were distributed to students. Using the student questionnaire, participants provided their name, age, fulltime or parttime enrollment status, current enrollment in an online or live algebra class, and previous enrollment in developmental mathematics classes (Tuckman & Harper, 2012). Students who denied consent returned the unsigned form or disposed of it themselves. Students who volunteered to participate in the study returned a signed consent form and a completed questionnaire to the faculty test administrator, their instructor, or the researcher. All documents were securely stored in a locked filing cabinet. Volunteers who were at least 25 years old and were currently enrolled in a college algebra class at the institution were included in the study. Collection of Data The initial data collection tool (Tuckman & Harper, 2012) was a categorical response questionnaire soliciting volunteer participants’ (a) name, (b) age, (c) enrollment status (fulltime/parttime), (d) enrollment in an online or live class, (e) previous enrollment in developmental mathematics (yes/no), and (f) consent to access the final college algebra grade. All informed consent and questionnaire data were collected within the 3 weeks following the 20 midterm exam. At the end of the semester, after posting of final grades, the researcher obtained participants’ final course grades from the cooperating mathematics department chairperson. Treatment of Data All four research questions were answered using a chisquare test for independence. This test “compares the observed frequencies or proportions of cases that occur in each of the categories with the values that would be expected if there was no association between the two variables being measured” (Pallant, 2010, p. 217). For Research Question 1, the independent variable was type of class, live or online. For Research Question 2, the independent variable was previous enrollment in developmental math status (yes or no). To answer Research Question 3, a variable representing four groups was computed: (a) those in a live class who previously had developmental mathematics, (b) those in a live class who did not previously have developmental mathematics, (c) those in an online class who previously had developmental mathematics, and (d) those in an online class who did not previously have developmental mathematics. This became the independent variable delineating type of class and developmental mathematics status. To answer Research Question 4, another variable was computed to be the independent variable delineating type of class and fulltime/parttime status: (a) fulltime students enrolled in a live class, (b) parttime students enrolled in a live class, (c) fulltime students enrolled in an online class, and (d) parttime students enrolled in an online class. Definitions of Terms The following terms are defined as they were used in the study: Blended or hybrid course. Allen and Seaman (2010) defined a blended or hybrid course as a “course that blends online and live delivery” (p. 5). In an online or blended class, a significant amount of the instruction is delivered online, and fewer live meetings are required 21 than are required for a live class. The Texas Higher Education Coordinating Board (THECB) defined a blended or hybrid course as a course in which between 50% and 85% “of the planned instruction occurs when the students and instructor(s) are not in the same place” (2012, p. 37). Community college. Cohen and Brawer (2008) defined a community college as “any institution regionally accredited to award the associate in arts or the associate in science as its highest degree” (p. 5). Developmental education. Developmental education includes “precollege, nondegree credit courses, interventions, tutorials, laboratories, and other means of assistance that are included in a plan to ensure the success of a student in performing entrylevel academic coursework” (Texas Administrative Code Title 19, Part 1, Ch. 4, Subch C. Rule §4.53). Distance education. The THECB (2012) defined distance education as “the formal educational process that occurs when the students and instructors are not in the same physical setting for the majority (more than 50 percent) of instruction” (p. 25). Distance education course. According to the THECB (2012), a distance education course is one in which the instructor and the students are not in the same location for more than half of the instruction. Distance education courses may be offered in a synchronous or asynchronous format to one or more locations, including the main campus, through “electronic, correspondence, or other means” (p. 25). Enrollment gap. An enrollment gap occurs when a student is enrolled for only part of an academic year (Pontes & Pontes, 2012). Live course. Live courses include traditional and webenhanced classes in which most of the instruction is delivered in person. According to Allen and Seaman (2010), up to 29% of the instruction in a live course may be delivered online. 22 Fulltime student. An undergraduate student enrolled in 12 or more semester credit hours in a fulllength semester is considered to be a fulltime student (THECB, 2012). Nontraditional student. Horn and Carroll (1996) indicated that age, particularly for students over 24 years old, “has become the defining characteristic for this population” (p. 3). The researchers also determined that age “acts as a surrogate variable that captures a large, heterogeneous population of adult students who often have family and work responsibilities as well as other life circumstances that can interfere with successful completion of educational objectives” (Horn & Carroll, 1996, p. 3). For the purposes of the current study, unless otherwise noted, a nontraditional student was defined as any student who was at least 25 years old. Online course. An online course is a class in which at least 80% of the content is delivered online. Online classes typically do not include any live meetings (Allen & Seaman, 2010). Parttime student. An undergraduate student enrolled in less than 12 semester credit hours in a fulllength semester is considered to be a parttime student (THECB, 2012). Semester credit hours (SCH). According to the THECB (2012), a semester credit hour is “a unit of measure representing an hour (50 minutes) of instruction over a 15week period in a semester or a trimester system or a 10week period in a quarter system” (p. 54). Texas education code. The Texas education code is the set of Texas state statutes regarding education (THECB, 2012). Texas Success Initiative. The Texas Success Initiative (TSI) is a legislatively mandated program that provides Texas public colleges and universities with flexibility in determining the college readiness of entering students. The TSI requires that students be tested in reading, writing, and mathematics skills and be provided with “appropriate counseling, advice, and 23 opportunities—such as developmental education courses or noncoursebased education” to improve college readiness skills if necessary (THECB, 2012, p. 63). TSI Assessment. The TSI Assessment is a program used by Texas public colleges and universities to assess the reading, writing, and mathematics skills of entering college students to determine individual preparation to begin freshmenlevel coursework (THECB, 2013c). Limitations This study was bound by the following limitation: 1. Participants selfreported certain data, including age, previous enrollment in developmental courses, enrollment in an online or live college algebra class, and parttime or fulltime enrollment status. Delimitations The following delimitations were applied to this study: 1. Participants were recruited from four campuses of one large community college in Texas. 2. The study included students age 25 and older who were enrolled in fully online and live college algebra classes; this study did not include students enrolled in hybrid college algebra classes. 3. The study included only those college algebra students who were enrolled in full semester, 16week college algebra classes. The study did not include students who were enrolled in 6week or 8week courses. 4. The study did not consider participants’ race, gender, socioeconomic status, or previous experience. 24 5. The study did not consider faculty status or preparation, such as fulltime or parttime status, level of degree attainment, experience, or training. Assumptions This study was conducted with the following assumptions: 1. The pilot study of the questionnaire ensured reliability and validity. 2. Participants responded to questionnaire items honestly and accurately. Organization of Dissertation Chapters The research study is organized in five chapters. Chapter 1 includes an introduction, problem statement, purpose of the study, research questions, hypotheses, significance of the study, method of procedure, definitions of terms, limitations, delimitations, and assumptions. Chapter 2 consists of an extensive review of the related literature, including the characteristics of nontraditional students, the prevalence and effectiveness of developmental education, the commonality of required college algebra, and the growth and perceptions of online college courses. Chapter 3 provides a detailed explanation of the method of procedure, and Chapter 4 includes a presentation and analysis of research findings. Chapter 5 contains a summary of the study, a discussion of the findings, conclusions, implications, and recommendations for future research. 25 Chapter 2 LITERATURE REVIEW The United States is shifting from a focus on college accessibility to outcomebased funding in an attempt to increase graduation rates (Bradley, 2012). At the same time, nontraditional students are enrolling in college at growing rates, increasing from 30% of the total undergraduate population in 1996 to 50% in 2006 (CarneyCrompton & Tan, 2002; Newbold, et al., 2010). The surge of online classes and degree programs has provided nontraditional students with access to a college education by removing scheduling and transportation obstacles. Developmental mathematics and college algebra classes, which have high failure rates, may prove to be a roadblock for nontraditional students who may have had little exposure to formal mathematics instruction for an extended period. The purpose of this literature review is to examine the related literature and lay a foundation for further research in this area. Nontraditional Students Characteristics of Nontraditional Students Students are generally referred to as adult or nontraditional if they are older than traditional college students and have not moved directly from high school into college. Nontraditional students are generally over the age of 24 and are more likely to have a spouse or livein partner and to be commuting more than five miles to school (Newbold, et al., 2010). Compton, Cox, and Laanan (2006) asserted that adult students often enroll in postsecondary education after a change in economic, employment, or marital status and are more likely than younger students to: pursue a specific vocational certification or degree; have a specific purpose, often related to career advancement, for attending college; 26 consider themselves to be an employee, spouse, or parent over being a student; enroll in distance education as a way to incorporate school into an already busy life; speak languages other than English; and leave college without a degree. (p. 74) According to Horn, Cataldi, and Sikara, “students who delay their postsecondary enrollment a year or more after high school differ fundamentally from those who enroll immediately” (2005, p. 33). In describing students who delay college enrollment, Horn, Cataldi, and Sikara maintained that Students who delay their postsecondary enrollment may do so for numerous reasons. Some may not be academically prepared to attend or have the financial resources necessary to enroll. Others may serve in the military, find employment, or start a family before enrolling. Students who delay enrollment for a long period of time are likely to enroll to advance in or change their careers. For whatever reasons students wait to enroll in college, those who do delay are at considerable risk of not completing a postsecondary credential when compared with their peers who enroll immediately after high school graduation. (2005, p. iii) Motivation and Confidence of Nontraditional Students Motivation is an important factor for all students, including adult learners. Shillingford and Karlin, (2013) found that while both intrinsic and extrinsic motivation affect nontraditional students’ motivation for learning, nontraditional students tend to be more intrinsically motivated than traditional students, meaning that they are more likely to engage in learning activities because it increases their feelings of competence and selfdetermination. Similarly, Swain and Hammond (2011) noted that nontraditional students’ motivation is strongly associated with their 27 sense of self, both the person they are now and the person they will become, and may be influenced by their desire to reinvent themselves or demonstrate their intellectual competence. Jinkens (2003) noted that nontraditional students may be very motivated to continue their studies by family obligations and employment factors, the circumstances that actually limit the amount of time they can devote to the endeavor. Jinkens also maintained that nontraditional students may be more committed to completing their studies than traditional students, even though they are often making more sacrifices as a result of that commitment. A faculty participant in Jinkens’ study alluded to this idea in the following quote, My experience with older students is that… they have… come to… realizations on their own. They’ve gone through their 20’s and they’ve kind of settled things out, and most of them recognize they have trade offs to do in life. Most of them, because they are older… want [to] be back in school. They’re here for a reason. They don’t like their jobs. They don’t want to be making minimum wage for the rest of their lives. They are far more committed. Their problems tend to be more of, “I can’t do it all.” (p. 83) Participants in Swain and Hammond’s (2011) study expressed similar notions and observed that nontraditional students committed to studies and contributed more to class activities than traditional students. The participants postulated that the older students were motivated to do their best because of the sacrifices they had made in deciding to attend college. These findings are consistent with a study of 300 randomly selected undergraduate students at a Midwestern university which found that nontraditional students selfreported slightly more overall motivation and significantly more intrinsic motivation than traditional students. Nontraditional students also tended to gain more satisfaction and increased interest in learning than their traditional peers (Bye, Pushkar, & Conway, 2007). These findings are 28 somewhat inconsistent with a study conducted by Justice and Dornan (2001), in which traditional and nontraditional students reported similar levels of motivation, study habits, selfefficacy, strategy use, and selfregulation, with older female students reporting the highest level of intrinsic motivation. Jameson and Fusco (2014) found that traditional and nontraditional students had similar levels of math selfefficacy in regard to functional math such as fractions and decimals, but not in regard to “areas of math that are perceived as more academic” (p. 313). Nontraditional students reported significantly lower levels of math selfefficacy in areas such as geometry and trigonometry, which may “stem from a lack experience with these tasks” (p. 313). Justice and Dornan (2001) noted no agerelated difference in the successful completion of the class. It is common for college students of all ages to consider dropping out of college, but the percentage of doubters and the reasons for doubting if they should continue their college career may vary between traditional and nontraditional students. A study of 172 psychology students enrolled in an English university revealed that slightly more than 43% of all participants doubted whether they should continue college enrollment (Xuereb, 2014). Whereas nearly 60% of traditional students reported doubting, only slightly more than 40% of nontraditional students doubted whether or not they should continue. Traditional students most commonly cited high academic workload and difficulties related to coursework as reasons for doubting continued enrollment in college. Nontraditional students, on the other hand, most commonly referred to outside responsibilities and personal or financial problems as primary reasons for doubting. Among all participants, “the most commonly cited reasons for continuing university studies was to achieve his or her end goal, closely followed by wanting to finish something he or she had started” (Xuebreb, 2014, p. 152). Traditional students, however, were more likely to report that 29 they decided to continue their college education because they wanted to finish what they started or that they had “experienced a positive change,” while nontraditional students were more likely to report that they continued due to support offered from university staff and support services (p. 152). Swain and Hammond (2011) found that nontraditional students may enroll or reenroll in college because they are more focused or more comfortable with themselves, or because they are in a better situation to attend college as an adult than they were or would have been as a traditionally aged college student. This supports Strage’s (2008) finding that older students and transfer students reported feeling more comfortable than traditional students with instructors, more confident in asking questions, and more likely to view instructors as a resource to help them learn. On the other hand, Justice and Dornan (2001) found that nontraditional students may also feel less confident than traditional students in using study skills effectively and in being able to succeed in college. HollisSawyer (2011) observed, however, that no relationship exists between older students’ perception of their ability and their actual performance. Academic Needs of Nontraditional Students Traditional and nontraditional students have different ideas about college courses and instructors. Strage (2008) studied 1,310 4year undergraduates and observed that older students (23 years or more) were tended to describe an ideal instructor as organized and flexible and the ideal course as organized, whereas younger students (1822) described an ideal instructor as funny and enthusiastic. For the traditional students, the ideal course was fun, easy, and active. Transfer students described the ideal course as being relevant to realworld and career interests. Older students tended to view college as a preparation for a career and valued coursework relevant to their career experience and aspirations (Compton et al., 2006; Strage, 2008). 30 Nontraditional students may study and learn differently than traditional students and may need assistance and guidance in developing effective study strategies (Justice & Dornan, 2001). Kenner and Weinerman (2011) charged instructors with helping adult students replace existing learning strategies with effective academic learning strategies, noting that adult students may resist abandoning learning strategies that have been effective in other areas of life. Kenner and Weinerman (2011) also indicated that older, goaloriented, students benefit from detailed syllabi and coursework that relates to other classes or to life outside of academia. Goddu (2012) recommended using situational or experiential learning, including roleplaying and problembased learning which allow adult students to use the new learning in practical ways. Instructorled lectures, still common in higher education, do not allow adult learners to integrate life experiences effectively into the lesson. According to Goddu (2012), all adult learning theories emphasize the importance of experience, and combining life experience with adult learning theory increases adult learning. Jesnek (2012) referred to a “digital divide” that exists between nontraditional students and college campuses. Nontraditional students are more likely than traditional students to lack the basic computer, word processing, and digital research skills that are expected in most college courses. Nontraditional students are also more likely to be unfamiliar with online portals, classroom management systems, and email, which are considered to be basic college skills. Learning these new skills is often very time consuming and may lead to increased anxiety and frustration for nontraditional students. Jesnek (2012) recommended the implementation of a noncredit essential computer skills course for students lacking the skills necessary for success in college. 31 Nontraditional Student Enrollment Nontraditional students are the fastest growing segment of the undergraduate student population, increasing from 30% of the total undergraduate population in 1996 to 50% in 2006, with 73% of all undergraduates possessing at least some characteristics of nontraditional students (CarneyCrompton & Tan, 2002; Newbold et al., 2010). Older students are significantly more likely than traditional students to be enrolled parttime as opposed to fulltime, which may be a reflection of older students’ increased work and family responsibilities (Calcagno et al., 2007b). In 2010, students 25 years of age and older comprised 64% of the parttime enrollment and 18% of the fulltime enrollment in U.S. 4year colleges and universities. In the same year, this group of students made up 52% of the parttime enrollment and 27% of the fulltime enrollment at U.S. 2year colleges (Chronicle of Higher Education, 2012). Factors contributing to a rise in nontraditional enrollment may include: (a) a weak economy, (b) global outsourcing, (c) aging Baby Boomers, (d) increasing technology, and (e) the need for new job skills (Jesnek, 2012). Horn, Cataldi, and Sikora (2005) noted that the longer students delayed college enrollment, the less likely they were to enroll fulltime or halftime, and the less likely they were to pursue a bachelor’s degree. Approximately 30% of students who delayed college entry by one year were pursuing a bachelor’s degree compared to 20% who delayed enrollment by 24 years, 10% who waited 59 years, and only 8% of those who delayed college enrollment by 10 years or more. Academic Success and Completion Rates for Nontraditional Students Newbold et al. (2010) found that nontraditional students maintained an average GPA of 3.5862 compared to an average GPA of 3.3772 for traditional students. This distribution represents a statistically significant difference on a 4.0 scale. In a small study of 63 female juniors and seniors, CarneyCrompton & Tan (2002) found that nontraditional female students 32 performed better academically than their traditional female peers, despite having increased family and work obligations and a limited support network. Nontraditional female students in CarneyCrompton and Tan’s (2002) study averaged 40.29 years, which may indicate that the older women had older children and a naturally increased selfefficacy due to their experience and maturity. Traditional students are more likely to be fulltime students and to graduate in less time than nontraditional students. Calcagno et al. (2007a) determined that traditional students were more likely to complete a community college degree or certificate in 17 trimesters than nontraditional students. Similarly, Newbold et al. (2010) found that 67.8% of nontraditional students take at least 5 years to complete a bachelor’s degree, compared to only 11.3% of traditional students. Pontes and Pontes (2012) identified dropout risk factors typically associated with nontraditional students including: independent student status, single parenting, having dependents, parttime enrollment, not being a high school graduate, fulltime employment, and delayed college enrollment. Over 70% of all U.S. undergraduates have one of these risk factors which classify them as being fairly nontraditional (Pontes & Pontes, 2012). After controlling for ability, determined primarily by placement test scores and enrollment patterns, Calcagno et al. (2007a) found that older students were more likely than their traditional counterparts to graduate from college. 33 Nontraditional students are significantly more likely than traditional students to experience an enrollment gap, meaning that they are enrolled in only part of an academic year (Pontes & Pontes, 2012). In 2008, 48.5% of all nontraditional students compared to only 15.8% of traditional students experienced a gap in enrollment during that academic year. Pontes and Pontes (2012) found that among nontraditional students, those who were enrolled parttime were more likely to experience an enrollment gap than those who were enrolled fulltime. In addition, nontraditional students who were financially independent were more likely to experience an enrollment gap than nontraditional students who were not financially independent. Pontes and Pontes (2012) noted an unexpected finding; however, that fulltime employment was not a significant risk factor for an enrollment gap among nontraditional students. Nontraditional students also tend to meet academic milestones, such as the accrual of a specified number of credit hours or completion of a specified percentage of the overall program, at a slower rate than traditional students (Calcagno et al., 2007b). Although reaching certain academic milestones increases the odds of degree completion for all students, Calcagno et al. found that nontraditional students were not impacted as much as their younger counterparts were by reaching or not reaching those milestones. For example, completing 20 nonremedial credits increased younger students’ likelihood of graduating by more than seven times. Older students who completed 20 nonremedial credits increased their chances of graduating by less than five times, however. Similarly, younger students who completed 50% of a program increased their odds of graduating by more than 15 times. Older students who completed 50% of the program, on the other hand, increased their chances of graduating by only 11%. In addition, older students were found to be less influenced by enrollment in developmental classes than were traditional age students. Calcagno et al. (2007b) maintained that nontraditional learners may benefit more 34 from flexible scheduling, varied course delivery formats, and childcare than from intense tutoring and advising that are often helpful to younger students. Texas Core Curriculum The Texas Core Curriculum is the general education requirement for Texas undergraduate students and provides the foundation for undergraduate degrees. The Texas Core Curriculum is determined by the THECB under the rules and guidelines of the Texas Education Code, determined by state legislation, and the Southern Association of Colleges and Schools Commissions on Colleges (SACSCOC), the regional accreditation body to which Texas is subject (THECB, 2011). Texas Education Code Section 61.821 defines the Core Curriculum as “the curriculum in arts, humanities, and sciences and political, social, and cultural history that undergraduate students of an institution of higher education are required to complete before receiving an academic undergraduate degree.” The Texas Core Curriculum accounts for one third of bachelor’s degree requirements , and once completed, is transferable as a unit to other Texas institutions (THECB, 2011). The SACSCOC requires a minimum of 15 semester credit hours (SCH) of Core Curriculum for an associate degree and at least 30 SCH for a baccalaureate degree, including at least one course from each of the following categories: humanities/fine arts, social/behavioral, and natural sciences/mathematics. The SACSCOC requires that these general education courses ensure a “breadth of knowledge” and do not “narrowly focus on those skills, techniques, and procedures specific to a particular occupation or profession” (SACSCOC, 2011, p. 19). The Texas Education Code 61.822, on the other hand, requires a minimum of 42 SCH of Core Curriculum for an undergraduate degree (Texas Education Code). Texas institutions must receive approval from the THECB to require a core curriculum in excess of 42 SCH (THECB, 2011). 35 The Education Advisory Committee (EAC), established in 2006, was charged with reviewing the Core Curriculum standards implemented in 1999. The EAC and the THECB determined that the Core Curriculum no longer served the needs of students and should therefore be revised to help ensure a smooth path to degree completion and preparation for 21st Century careers (THECB, 2011). The EAC also determined that the 1999 Core Curriculum was not sufficiently aligned with SACSCOC (2011) Core Requirement 2.7.3 which states that the Core Curriculum “…ensures breadth of knowledge…” and “…the courses do not narrowly focus on those skills, techniques, and procedures specific to a particular occupation or profession” (p. 19). One goal of the revised Core Curriculum, which was implemented in 2014, is to work within the framework required by SACSCOC and Texas statute and to move away from a set of isolated skills and toward a broader unit of interdisciplinary knowledge, skills, and competencies to include: (a) communication skills, (b) critical thinking skills, (c) empirical and quantitative skills, (d) teamwork, (e) social responsibility, and (f) personal responsibility (THECB, 2011). In the area of mathematics, which has a three SCH requirement, this revision meant that the previous objectives focusing primarily on quantitative literacy in realworld situations would be revised to include mandated objectives related to critical thinking, communication, and empirical and quantitative skills. Developmental Education History of Postsecondary Developmental Education Postsecondary developmental education in the United States began at Harvard College in 1636 as an effort to provide a literate pool of ministers to the colonies (Dotzler, 2003). During the early to mid1800s, private colleges, widely accessible to men who could bear the expense of higher education, employed tutors to support students who were underprepared for college, 36 primarily due to the period’s lack of available secondary schools. By 1889, developmental education was available at over 80% of postsecondary institutions (Dotzler, 2003). Cost of Developmental Education Developmental education cost the United States $1.3 billion during the 20042005 academic year and in excess of $2 billion per year by 2012 (Pretlow & Wathington, 2012). State expenditures for developmental programs have also increased over time. Developmental education accounted for $206 million of the 20062007 Texas biennium budget. Controlling for inflation, this represented a 5.5% increase over the $153.4 million spent on developmental education during the 19961997 biennium, when 2.25% of all Texas higher education funding was used for developmental programs (Pretlow & Wathington, 2012). Inconsistency among Developmental Education Programs Despite the cost to the American public, developmental math courses have become a barrier to degree completion, as a large proportion of students who enroll in the developmental mathematics sequence never complete it and therefore never earn a college credential (Bonham & Boylan, 2012). Some states, including Virginia, Texas, North Dakota, Louisiana, Colorado, and Alaska have created task forces to research the need, effectiveness, and objectives of developmental education and to develop an action plan or policy to address, correct, or improve these programs (Wilson, 2012). States such as Tennessee, North Dakota, New York, Missouri, Minnesota, Louisiana, Florida, and Colorado have adopted policies preventing 4year colleges and universities from offering developmental programs. In addition, three states, Nevada, South Carolina, and Nebraska, have eliminated state funding for developmental education at 4year colleges and universities (Wilson, 2012). At a time when budgetary constraints and state policies force 4year institutions to refer underprepared students to community colleges for their 37 developmental preparation, some 2year colleges no longer offer the lowest level developmental classes and have set limits on the amount of time students may take to complete the sequence (Pretlow & Wathington, 2012). There are no national standards for college readiness skills, but 35 states, including Texas, have policies to guide student placement in developmental courses (Wilson, 2012). Assessment instruments and score requirements vary and may not provide a true assessment of the student’s actual knowledge and skills (Bailey, 2009). Donovan and Wheland (2008) reported a high correlation between COMPASS I and ACT mathematics scores and success in intermediate algebra, but noted that although females may score lower on placement tests, they are significantly more likely than males to be successful in intermediate algebra. The Western Interstate Commission for Higher Education (Lane, Michelau, & Palmer, 2012) reported that the common practice of placing students in developmental courses based on one standardized test is a barrier to adult degree completion. Research indicates 4050% of these students could have successfully completed the entrylevel or “gateway” course without remediation. Assessment scores and the reliability of these scores in measuring student knowledge and skills may be influenced by a student’s failure to realize the importance of the placement test and by a lack of preparation and review for the test (Charles A. Dana Center et al., 2012). Bailey, Jeong, and Cho (2010) found that students originally directed to developmental courses, who chose instead to take entrylevel classes, had a slightly lower success rate than students not referred to developmental education, but a significantly higher success rate than students who did enroll in developmental courses, because only a small percentage of developmental education students ever enrolled in entrylevel classes. 38 Students who are successful in developmental mathematics may catch up with collegeready peers, but failing a developmental math course has been associated with significantly negative consequences (Fike & Fike, 2012). In a study of 3,476 firsttime college students, Fike and Fike found that students who passed developmental mathematics during their first semester had GPAs and retention rates similar to those of students who were academically prepared for college math when they started college. Students who needed developmental mathematics but did not enroll in it during their first semester had lower GPAs and lower retention rates than students who passed developmental mathematics their first semester, despite the fact that the group that delayed enrollment was better prepared than those who enrolled in the developmental course during their first semester. Students who failed developmental mathematics had lower overall GPAs than the other groups and were more than 80% less likely than their collegeready peers to return to college the following fall (Fike & Fike, 2012). Developmental Education Standards in Texas Although the use of college readiness assessments and results vary throughout the United States, the Texas Administrative Code (TAC) standardized the assessment and placement standards for all incoming students at Texas higher education institutions beginning with the 20132014 academic year (TAC). The TSI (Texas Success Initiative) Assessment is the only college readiness assessment approved by the THECB for use in Texas colleges and universities. With very specific and clearly defined exceptions, all incoming Texas college students are required to take the TSI Assessment. In addition, students are required to participate in a preassessment activity which includes information about the importance of the TSI test, examples of the test questions, an explanation of developmental education options, and information about resources available to help students succeed in college (TAC Title 19, Part 1, Ch. 4, Subch C, 39 Rule §4.55). Furthermore, all Texas higher education institutions are required to follow guidelines for referring students to developmental coursework or placing them in entrylevel classes. Texas higher education institutions are required to follow specific TSI passing standards which may not be raised or lowered. While TSI assessment results may not be used to deny student admission to an institution or program, the results are a required component of a holistic approach to course placement. The holistic approach also considers factors such as high school GPA, prior coursework, noncognitive factors such as motivation and selfefficacy, and familylife issues such as job responsibilities and childcare (TAC Title 19, Part 1, Ch. 4, Subch C, Rule §4.55). Texas institutions are required to provide an individualized academic plan to support students who do not meet the minimum TSI standards required to begin entrylevel coursework. The plan must include career advising, developmental education options, information about support services, a degree or program plan, regular contact with an advisor or other designee, registration information, and differentiated placement (TAC Title 19, Part 1, Ch. 4, Subch C, Rule §4.58). In addition, developmental coursework in Texas higher education institutions must be based on researchbased practices in assessment, differentiated instruction, and the integration of instructional technology. Developmental students in Texas also benefit from specialized support services, noncoursebased education interventions, and specially trained faculty (TAC Title 19, Part 1, Ch. 4, Subch C, Rule §4.62). Referral Rates and Correlations College students are referred to developmental courses in high, but varying, percentages. The Charles A. Dana Center et al. (2012) found that 50% of all U.S. undergraduate students and 70% of all U.S. community college students enroll in at least one developmental class. Parker 40 (2012) noted that 25% of students seeking a bachelor’s degree and 25% of students enrolled in a 4year college or university are placed into developmental coursework while 60% of students seeking an associate’s degree and 50% of students enrolled in a community college are placed into developmental classes. Pretlow and Wathington (2012) found that onethird of all firsttime college freshmen and up to 60% of all community college students require developmental education and that between 1996 and 2012, community colleges quadrupled the number of developmental classes offered in a distance education format. Bahr (2010) reported a high degree of correlation between mathematics and English deficiencies and remediation. Controlling for second language learners, 69% of students requiring no mathematics remediation also required no English remediation, whereas only 12% of students requiring the most intense mathematics remediation required no English remediation. The severities of the deficiencies were also found to be correlated. As severity in one subject increased, the likelihood of severity in the other subject also increased. Only 20% of students who began college deficient in mathematics and English, compared to 58% of students who began with no deficiencies, eventually reached entrylevel proficiency in both subjects (Bahr, 2010). A Barrier to Degree Completion The Charles A. Dana Center et al. (2012) suggested that developmental instruction serves to keep students out of entrylevel courses rather than increasing the chances of enrollment and success in courses such as college algebra. Evidence suggests that most developmental college courses do not include the teaching of paper writing skills or strategies designed to help students in areas such as test taking, note taking, and coping with the demands of work, family, school, and social expectations. In a study of 756 community college students, Wolfle (2012), found 41 that firstsemester students who enrolled in developmental mathematics were retained from first to second year at rates comparable to firstsemester students who enrolled in entrylevel mathematics. Over 72% of the developmental mathematics students in the study, however, never enrolled in an collegelevel mathematics course, which is consistent with research indicating that 87% of developmental mathematics students in Texas community colleges never complete entrylevel mathematics (Complete College America, 2013). According to the Charles A. Dana Center et al. (2012) college success is correlated to early enrollment in the student’s academic field. Developmental course sequences delay entry into these major area courses and increase the dropout risk. More than half of the students who enter concentration area classes during the first academic year either graduate from the community college or transfer to a 4year institution within five years. The 5year graduation or transfer rate drops to 20% if enrollment in major area classes is delayed until the third year of college enrollment (Charles A. Dana Center et al., 2012). Community college students who successfully complete the developmental sequence earn associate degrees or transfer to another institution at similar rates to students not requiring remediation, regardless of the number of developmental courses or subjects required (Bahr, 2010). Only 2533% of all developmental mathematics students ever complete the developmental mathematics sequence, however, and only 16% of students who begin three levels below college mathematics complete the developmental sequence within three years. Seventytwo to eighty percent of students requiring remediation never enroll in an entrylevel course (Bahr, 2008; Charles A. Dana Center et al., 2012; Templin, 2011; Wolfle, 2012). High attrition rates in developmental course sequences are linked to lower graduation rates. In a study of 85,894 students from 107 California community colleges, Bahr (2008) found 42 that 81.5% of students who enrolled in developmental mathematics did not earn an associate’s degree or transfer to another institution within eight years. This is consistent with the studies conducted by the Charles A. Dana Center et al. (2012) and Parker (2012) which indicated that approximately 75% of community college developmental education students fail to earn a degree or to transfer within eight years. Parker (2012) also found that only 32% of all students enrolled in developmental education earn a bachelor’s degree in six years as opposed to 58% of students who never enrolled in developmental classes. Developmental Mathematics and Age Developmental education enrollment is high among older students. Nearly half of all Texas college freshman ages 25 or older require at least one developmental class. Of these, only 13% of those enrolled in a community college, and 19% of those enrolled in a 4year college, go on to complete the associated entrylevel course (Complete College America, 2012). Older students are also significantly more likely than younger students to be placed in the lowest levels of developmental courses, especially in mathematics. This is of particular concern for nontraditional students as Le, Rogers, and Santos stated, “Students who hit a roadblock in the lowest levels of developmental mathematics are the most at risk for giving up on ever earning a postsecondary credential” (2011, p. 2). A study of 500 university students who failed to meet requirements to enroll in college algebra found that older students were significantly more likely than traditional students to be placed into the lowest level of developmental mathematics (Walker & Plata, 2000). An analysis of 35,073 students found that nontraditional students, students 25 years of age and older, scored an average of 87 points lower on mathematics placement exams but 29 points higher on verbal skills assessments than traditional students. Researchers noted that the difference in scores might 43 have been due to a combination of nontraditional students’ extended time away from formal mathematics instruction while still being required to use communication skills in the work place and social settings (Calcagno, et al., 2007a). Penny and White (1998) studied 1,475 developmental mathematics students from three universities and found that student age had a weak positive correlation with success in the highest levels of developmental mathematics, and Calcagno et al. (2007b) found that, while enrollment in developmental mathematics decreased the probability of college graduation for all students, older students seemed to be less negatively impacted than younger students. Other researchers have reported comparable success and persistence rates for traditional and nontraditional students who enroll in developmental mathematics courses (Little, 2002; Walker & Plata, 2000; Wolfle, 2012). Calcagno et al. (2007b) suggested that older students who are not seriously deficient in math or English may benefit from taking shorter refresher courses instead of fullsemester remedial courses prior to enrolling in collegelevel courses. Predicting Success Doyen (2012) found that for community college students who had completed intermediate algebra, the highest level of developmental mathematics, success in college algebra was highly correlated to the intermediate algebra assessment score and the intermediate algebra course grade. Doyen (2012) found that students who scored the highest on the intermediate algebra assessment and those who earned the highest grade in the intermediate algebra course were the most successful in college algebra. Although Doyen’s study included only 134 purposefully selected students who enrolled in a developmental mathematics course in the previous calendar year, the results are consistent with Penny and White’s (1998) conclusion that for developmental mathematics students, success in the highest level of developmental 44 mathematics is the strongest predictor of success in college algebra. Conversely, Doyen (2012) determined that enrollment in prealgebra, the second level of developmental mathematics, had a strong negative correlation with success in college algebra. Students who enrolled in prealgebra were less likely to be successful in college algebra than students who had been enrolled in intermediate algebra but not prealgebra. This finding is consistent with Donovan and Wheland’s (2008) finding that students who were placed directly into intermediate algebra were more successful in the course than students who previously enrolled in a lower level developmental mathematics class. Although this pattern may be an expected outcome, it is important to note that the objective of the lower level course is to prepare students for intermediate algebra. A study of 125 community college developmental mathematics students revealed a negative relationship between mathematics anxiety and achievement scores. Woodard (2004) found no significant variance in mathematics anxiety between traditional and nontraditional students but noted that achievement scores for both groups decreased as mathematics anxiety increased. The Charles A. Dana Center et al. (2012) noted that the shame and disappointment associated with repeating high school curriculum, often with high school instructional strategies, leads to higher rates of attrition among developmental students. Nontraditional students, however, are less affected by the negative impact of enrollment in developmental classes, especially developmental mathematics, than are traditional students (Calcagno et al. 2007b). Affective factors also influence the success of developmental mathematics students. Chadwick’s (2013) study determined that effective developmental mathematics instructors are aware that they are the most important variable in the learning environment. Content knowledge and the ability to teach were found to be of secondary importance to affective qualities such as 45 treating students with respect, developing positive relationships with students, providing an encouraging and nonjudgmental environment, reducing math anxiety and feelings of inadequacy, and being patient. In addition, the most successful developmental mathematics instructors were identified as those who maintained high standards, encouraged students to take responsibility for their learning, focused more on learning than on the students’ lack of knowledge, and were engaging. Developmental mathematics students were also found to be more successful when they were enrolled in smaller classes, were able to use a math lab, and had multiple learning opportunities such as a review of content, homework assignments, and varied assessments Chadwick, (2013). Redesigning Developmental Mathematics Programs “For many community college students, the traditional course delivery model— students attend a semesterlong lecture class several times per week—does not lead to success in developmental math” (Le, Rogers, & Santos, 2011, p. 3). As a result, colleges and universities are exploring alternate course delivery models, including accelerated classes, math labs, relating specific math skills to students’ intended majors, and offering technology enhanced instruction to support students and move them more quickly into creditbearing courses. Le, Rogers, and Santos argued that statewide initiatives would be necessary to establish, maintain, and reproduce successful developmental mathematics programs and recognized the THECB for providing funding and support to develop “innovative and effective developmental education programming” (p. 10). Research indicates that developmental programs are not an effective method of preparing students to be successful in entrylevel mathematics (Bailey, 2009). The Charles A. Dana Center et al. (2012) have developed a set of seven Core Principles to redesign and repurpose 46 developmental classes. These principles focus on acceleration over remediation and call for students to be placed in major courses early in their college career. The principles also call for multiple assessment measures before placing students in classes and requiring academic support classes as corequisites rather than prerequisites to college algebra. The Charles A. Dana Center et al. (2012) recommended either a onesemester corequisite class to support students through gateway classes such as entrylevel mathematics, or a oneyear plan specifically designed to support significantly underprepared students through entrylevel courses over the course of a full year. Research indicates that students who participate in the accelerated model are two to four times more likely to complete the entrylevel class than students who are placed one to two levels below college mathematics (Charles A. Dana Center et al., 2012; Complete College America, 2013). In a similar study, the National Center for Academic Transformation partnered with 38 community colleges to redesign developmental mathematics courses using technology and an acceleration model in which students participated in small course modules targeting their specific areas of weakness. This approach led to a 30% reduction in the cost of instruction and 31% increase in the student success rate (Templin, 2011). The Charles A. Dana Center et al. (2012) concur with the principle of individualized instruction, stating that developmental and support classes should be designed to meet the needs of students from particular majors, instead of attempting to prepare every student for college algebra. College Algebra Why College Algebra? Why is college algebra important? Hagerty, Smith, and Goodwin (2010) claimed that the processes and concepts learned in college algebra prepare students to be successful in subsequent 47 coursework outside the mathematics department. After extensive collaboration with representatives from “partner disciplines” including science, social sciences, and the arts, the Mathematics Association of America (MAA) found that representatives from the partner disciplines largely agreed that entrylevel college mathematics classes should be relevant, pleasant, and thoughtful experiences that develop students’ mathematical and logical reasoning skills and prepare them to become knowledgeable citizens and employees. Representatives from the partner disciplines also asserted that entrylevel college mathematics courses should provide a foundation for courses in other fields, develop student’s ability to communicate mathematical ideas, and should promote enrollment in additional mathematics courses (Ganter & Haver, 2011). In response to these findings, the MAA published college algebra guidelines designed to support the other disciplines. These guidelines include fundamental experience, course goals, competencies, and an emphasis on pedagogy (Ganter & Haver, 2011, pp. 4546). The MAA maintained that college algebra should provide students with fundamental experience that emphasizes algebraic reasoning and problem solving in the mathematics course, in other coursework, and in life outside of academia. The fundamental experience portion of the guidelines also indicated a need for students to address realworld problems through the creation and interpretation of mathematical models. In addition, the MAA recommended that students formulate, solve, and analyze problems using a variety of methods including mental strategies, pencil and paper, and technology (Ganter & Haver, 2011, p. 45). Although the MAA college algebra course goals included strengthening students’ algebraic and quantitative skills required in other disciplines, they also focused on the development of related skills. The MAA course goals called for a “meaningful and positive, intellectually engaging, mathematical experience” that allows students to collaborate, explore, 48 and communicate mathematical ideas (Ganter & Haver, 2011, p. 45). The MAA also called for the development of student confidence, the ability to use technology to solve problems, and the encouragement of students to take additional mathematics classes. The MAA’s college algebra competencies included problem solving in realworld situations. According to the guidelines, college algebra should emphasize the creation, interpretation, and revision of models to solve problems and students should develop personal problem solving strategies such as rereading a problem, sketching a diagram, identifying variables, and determining the plausibility of a solution. In addition, the MAA maintained that students should be expected to understand and use functions, rate of change, equations, and appropriate data collection to model and solve realworld problems (Ganter & Haver, 2011, p. 46). Finally, the MAA college algebra guidelines called for an emphasis on pedagogy and a variety of assessment tools and methods. Instructors were encouraged to create an environment “conducive to exploratory learning, risktaking, and perseverance,” to “encourage a conceptual understanding of mathematics,” to provide studentcentered learning opportunities, and to utilize technology such as calculators and spreadsheets. According to the guidelines, assessments should be designed to measure mastery of the course competencies including problem solving, mathematical arguments, and communicating mathematical ideas orally and in writing (Ganter & Haver, 2011, p. 46). The Argument against College Algebra for All College algebra is often a required element of general undergraduate education or core requirements, with up to 98% of students on some college campuses taking the class as a requirement rather than as an elective (Herriott & Dunbar, 2009). Introductory college 49 mathematics classes such as college algebra may serve as a roadblock to degree completion, especially for students who are uninterested in the material or who have mathematics related anxiety based on prior experience (Thiel et al., 2008). Although a vast majority of college students are required to take college algebra, nearly half of the 1,000,000 annual enrollees fail the course, and only 20% reenroll within the next 11 to 12 semesters (CortesSuarez & Sandifer, 2008; Gordon, 2008; Herriott & Dunbar, 2009; Thiel et al., 2008). A small study of two community colleges in Georgia revealed that college algebra and math modeling, the lowest creditbearing mathematics course at one of the institutions, had a higher rate of withdrawals and final grades of D and F than did freshman composition, American government, biology, and macroeconomics (Herriott & Dunbar, 2009). The rate of college enrollment has grown at approximately five times the rate of the U.S. population since the end of World War II (Gordon, 2008). Whereas college students were once the most academically and mathematically qualified students prepared for an algebraically intense calculus course, this is no longer the case. College algebra and precalculus classes were originally intended to prepare weaker students for calculus. Gordon (2008) found that although fewer than 15% of college algebra students intend to take calculus, the curriculum and focus of college algebra classes have remained largely unchanged over the past 50 years and do not sufficiently prepare students for the digital world. Herriott and Dunbar (2009) found that 31.9% of the nearly 1,500 college algebra students at a Midwestern state university went on to register for calculus for management and social science majors, and only 11.2% enrolled in Calculus I. Enrollment in Calculus II and III was even lower at 4.2% and 1.3% respectively. College algebra is the terminal mathematics class for a majority of students and may not adequately meet the needs of most college students (Gordon, 2008; Herriott & Dunbar 2009). 50 The Charles A. Dana Center et al. (2012) maintained that college algebra should not be a required course for students when other college mathematics classes would be more appropriate for a specific field of study. Gordon (2008) maintained that it is a disservice to most students to continue the practice of using lowerlevel general education mathematics courses such as college algebra to serve the needs of mathematics majors who comprise only a small percentage of the student body. High school students are taking more mathematics classes than before, but are referred to developmental education in increasing numbers (Gordon, 2008). High school teachers focus more on concepts and problem solving and incorporate more technology and calculator usage into their classes. A smooth transition to college mathematics has remained elusive, however, as placement tests and college coursework continue to focus on processes, formulas, and traditional mathematics (Gordon, 2008). In addition, although enrollment in college calculus has remained steady or declined slightly since the late 1990s, high school dual credit and AP calculus completions have increased at an average annual rate of 8% over the same period. Consequently, today’s most prepared students do not need firstyear college calculus. It is possible that college calculus will eventually become more of a developmental course than an entrylevel mathematics class (Gordon, 2008). College algebra is financially lucrative for colleges and universities. It is reportedly one of the least expensive and most frequently offered creditbearing mathematics classes, often taught by parttime faculty and teaching assistants. Gordon (2008) asserted, however, that mathematics departments exist to serve the needs of other departments by preparing students for classes in other disciplines. If college algebra and other mathematics classes do not meet the needs of these other departments, then the departments may cease to require these courses and 51 the mathematics department will be left with little more than developmental course offerings. Nontraditional Student Success in College Algebra HollisSawyer (2011) found that undergraduate students over the age of 40 reported higher levels of mathematics and testrelated anxiety and lower levels of confidence in their ability to be successful in mathematics. Believing that a negative stereotype exists about older students’ mathematics abilities may be a contributing factor to the reduced confidence levels, even when no significant difference exists in actual mathematics performance. Studies investigating a correlation between student age and success in college algebra have produced varying results, with success being defined as completing the course with a grade of A, B, or C. Wolfle (2012) found that students aged 23 and older were 1.36 times more likely to succeed in college algebra than their 1722 yearold classmates. Penny and White (1998) observed a weak positive correlation between student age and improved performance in college algebra but noted that most of the students were under 29 years, and that there was no evidence of improved performance for students who were significantly older than traditional age students. Doyen’s (2012) study of 134 community college students who had completed intermediate algebra in the previous calendar year found that 79% of enrolled students 25 and over completed college algebra successfully, compared to 66% of students ages 1822. The canonical structure coefficients, however, revealed a weak correlation between age and success in college algebra. Conversely, Calcagno et al. (2007b) found that older students, who had taken developmental mathematics courses enrolled in and passed college algebra at a lower rate than did traditional age students who had taken developmental mathematics courses. 52 Course Scheduling, Student Age, and Success in College Algebra Researchers have examined the correlations between course scheduling, student age, and success in college algebra. Gallo and Odu (2009) found that, regardless of age, students enrolled in classes that met two or three times per week were significantly more successful than students enrolled in classes that met only one time per week. Reyes (2010) examined the pass rates for students enrolled in 8week and 16week college algebra classes at a metropolitan community college in the United States. He found that 2330yearold students performed significantly better in the 16week course than in the 8week course. Course length was not a significant factor for 3140yearold students. Redesigning College Algebra The Western Interstate Commission for Higher Education (WICHE; Lane, Michelau, & Palmer, 2012) identified redesign of gateway classes, especially entrylevel mathematics, as a “promising practice” (p. 46) for reducing the barriers to adult degree completion. According to Gordon (2008), students need more exposure to and more practice with exponents and logarithms throughout their mathematics course rather than isolating them into only a chapter or a few sections; more practice with concepts and processes that carry over into other disciplines; more nonroutine, conceptual problems that have realworld applications, multiple perspectives, and multiple ways to solve the problem; realistic problems to solve rather than artificial problems that do not transfer to real situations; and an in depth conceptual understanding of algebraic reasoning and processes so that the skills will transfer to other disciplines and apply to the real situations. 53 Technology plays an important role in the course redesign for college mathematics courses. Butch and YuJu (2010) found that students who enrolled in classes using a computerized, masterybased, textbookcoordinated homework system performed better on exams than students enrolled in classes that used the traditional pencil and paper homework method. This concurs with previous findings by Hagerty and Smith (2005) who noted that students enrolled in evening classes, typically nontraditional students, did not show the same benefit from the computerized masterybased homework system and reported having less time than daytime students to log into a computer to complete the assignments. Instructors in Butch and YuJu’s (2010) study reported that the computerized homework helped the class move more smoothly, improved class discussions, reduced grading time, and allowed students to track their grades online. Although students in the computerized homework classes performed better on exams, the paper and pencil homework grades were a better predictor of exam grades, likely due to instant feedback and the allowance of multiple attempts to answer computerbased homework problems. Butch and YuJu, (2010) also noted a higher retention rate in the computerized homework classes. Eightysix percent of the students in the computerized homework classes finished the class, compared to 58% of the students in the pencil and paper classes. The University of MissouriSt. Louis also used technology to redesign college algebra to create a more active learning environment (Thiel et al., 2008). Lecture sections were reduced from three 50minute sessions per week to one 50minute session per week. The remaining class periods were replaced with time in the computer lab which allowed students to participate in active, handson, and collaborative learning. Software that complimented the textbook provided instructions, practice, tutorials, and guided solutions. Students were allowed to retry homework problems as many times as they desired, were rewarded with instant feedback and higher grades 54 when they answered problems correctly, but were held firmly accountable for deadlines. Weekly quizzes, unit tests, and a final exam were also completed in the lab. Instructors used class lecture time to introduce new or difficult concepts, guiding students through the course, and reviewing for upcoming tests. Students learned the mathematics by doing it rather than by listening to it. Student attitudes regarding mathematics improved and the pass rate increased from 55% to over 75% in three years. These results are consistent with the results of a similar study in which the mathematics faculty at a regional Midwestern university worked with faculty from the psychology department to redesign college algebra courses in a similar fashion (Hagerty et al., 2010). In addition to increasing the pass rate from 54% to 75% between 2002 and 2006, the university also noted a 0.5% increase in overall GPA, and a 300% increase in trigonometry enrollment. Although the efforts to redesign college algebra have been successful, they have not been free of challenges. Thiel et al. (2008) noted that barriers to course redesign included funding; instructor release time to design curriculum and test the program; and resistance to change. Online Classes Growth of Online Instruction Although the total enrollment in U.S. higher education dropped by 0.1% between the fall of 2010 and the fall of 2011, the percentage of college students enrolled in at least one online class actually increased by 9.3% during the same period (Allen & Seaman, 2013). In 2011, some 6.7 million postsecondary students, or 32% of all U.S. higher education students, were enrolled in at least one online class. This increase represents a compound annual growth rate of 17.3% over the 1.6 million U.S. college students enrolled in at least one online class in the fall of 2002 (Allen & Seaman, 2013). 55 In 2011, 91% of all U.S. 2 year colleges offered online classes (Parker, Lenhart, and Moore, 2011). By 2012, 62% of all U.S. postsecondary institutions, or 70% of all public and 48% of all private institutions, offered at least one completely online degree program and over 86% of all U.S. higher education institutions offered at least some online course options (Allen & Seaman, 2013). In addition, a 2011 report by Parker et al. indicated that 58% of colleges that offer online courses also offer at least one completely online degree program and 88% of residential colleges that offer online courses make those courses available to students who live on campus. Approximately 46% of U.S. students who graduated from college between 2001 and 2011 had taken at least one online course. Distance education, including enrollment in online courses, has also increased in Texas. In the fall of 2012, distance education accounted for 12.8% of the total Texas public higher education enrollment. This number represents a steady increase in fall to fall distance education enrollment percentages since 2002, when distance education comprised 2.45% of the total public postsecondary enrollment in Texas (THECB, 2013a). During the same period, online enrollment in Texas higher education courses has grown from representing 0.4% of the total enrollment in 2002, to accounting for 6.03% of the total enrollment in 2012 (THECB, 2013a). Perceptions of Online Instruction A survey of higher education leaders revealed a disconnect between their views and the opinions and practices of postsecondary institutions, presidents, faculty, and students (Allen & Seaman, 2013). The percentage of U.S. higher education leaders who viewed online instruction as a critical aspect of their institution’s longterm plan increased from less than 50% in 2002 to over 69% in 2012. However, only 60% of academic leaders from institutions offering entirely online programs and 30% of those from institutions offering online classes thought that their 56 institution’s strategic plan adequately reflected the importance of online instruction. While 77% of academic leaders viewed online instruction as equal to or better than live instruction, only 30% believed that faculty view online instruction as valuable and legitimate, and 57% remained neutral about faculty acceptance (Allen & Seaman, 2013). In addition, although 51% of university and college presidents believed that online courses are equal to or better than live courses, presidents of public institutions are more likely to believe this than presidents of private institutions, and only 29% of American adults agree (Parker et al., 2011). Whereas 39% of adults who have taken online classes described those classes as being of equal educational value to live courses, only 27% of adults who have not taken online classes subscribed to the same opinion (Parker et al., 2011). Advantages and Disadvantages of Online Instruction Students choose to enroll in online classes for a variety of reasons. Harris and Martin (2012) found that the most commonly reported reasons for taking online classes were related to time and location factors. Nearly twothirds of the online students included in Harris and Martin’s study indicated that the ability to complete assignments at a convenient time was a primary motivation for enrolling in an online class. Slightly over half of the online students in the study indicated that they enrolled in online classes because the commute to campus was too far or inconvenient. Fortyfive percent of the online students indicated that the ability to earn a degree and meet family obligations was a primary motivating factor for enrolling in online classes and an equal number cited the ability to take classes and meet employment requirements as an important factor. Other motivations for enrolling in online classes included course scheduling conflicts (27%), the ability to take summer classes while traveling (17%), and a preference for online learning (17%). These findings are consistent with Mahoney’s (2009) 57 conclusion that “Flexibility was the main reason participants enrolled in the online classes. The online classes allowed participants to have more control over their school and work schedules” (pp. 8182). While some participants in Mahoney’s study indicated that the flexibility of the online course increased the time they could work, others indicated that it allowed them to use their time more efficiently, which included allowing them to study at times that were quiet and they could work in solitude. Ghaffari (2011) identified several advantages to online classes from the student perspective. Primary among these was flexibility in both scheduling and location. Ghaffari maintained that online classes allow students to adjust their school schedule around life preferences and responsibilities, rather than requiring them to adjust their life to meet the demands of a specified class schedule. For some students, this may be related to the desire to avoid early morning classes. For others, including nontraditional students, online classes may be the only option that fits their already demanding schedule. Ghaffari noted that online courses allow students to take classes almost anywhere around the globe without requiring them to relocate or to commute to a specified location. Ghaffari also noted the additional advantages of increased access to class notes and lecture transcripts and the increased possibility of instructional technology and multimedia in online classes. Although administrators, faculty, and students cite advantages to online higher education opportunities, there are also disadvantages and barriers to online instruction. Student selfdiscipline is viewed as a key barrier to online classes. Ghaffari (2011) noted that online classes require students to have superior time management, selfregulation, and communication skills. In addition, 88% of academic leaders in 2012 indicated that online courses necessitate more student selfdiscipline than live classes (Allen & Seaman, 2013). Ghaffari (2011) and Harris and 58 Martin (2012) found that students in online classes may experience decreased communication with instructors and classmates, reduced access to tutoring services, and the inability to transfer online coursework into traditional degree programs. Participants in Mahoney’s (2009) study also reported feeling disappointed with the lack of technology, redundancy in assignment requirements, unclear assignment expectations, and limited access to the instructor. Institutional barriers to online instruction include: (a) higher attrition rates in online classes, (b) lack of employer acceptance of online programs, and (c) lack of faculty acceptance of online instruction. The Online Student Online students tend to be older than traditional live students and have typically earned more credit hours than students enrolled in the live versions of the same class (Wilson & Allen, 2011; Harris & Martin, 2012). A survey of online students indicated that they most frequently experienced written assignments, clear grading policies, multiple choice assessments, timely responses to emails and phone calls, and peer communication in online discussion boards (Harris & Martin, 2012). Infrequent experiences cited by online students included the availability of synchronous class discussions, video lectures, proctored tests, effective use of multimedia instructional tools, and interaction with instructors via the online message boards. Successful Versus Unsuccessful Online Students Wilson and Allen (2011) found cumulative GPA to be the best predictor of success for online and live students, but research suggests other factors may predict student success in online classes. Fetzner (2013) found that the most successful online students were at least 25 years of age, registered for classes at least 5 weeks prior to the start of the semester, and had previously earned a higher number of credit hours. Online students also identified the availability of technical support as important in successful completion of online courses (Beaghan, 2013). 59 A survey of 488 community college students who had previously been unsuccessful in at least one online class indicated that they did not know what to expect in an online course, how to get assistance in the class, or how much time and organization would be required to be successful (Fetzner, 2013). Nearly half of the participants revealed that they did not realize that they were required to begin the course on a specific date. The study also revealed that nearly 20% of the students surveyed attributed their failure to falling behind in class and not being able to complete all of the assignments. Approximately 28% indicated that personal problems, work, and family responsibilities were the primary reasons they were unsuccessful in the online course. Additionally, approximately 21% of the unsuccessful online students attributed their failure to an aversion to the online format, distaste for the instructional style, or “too many technical difficulties” (Fetzner, 2013, p. 15). Other participants indicated that that the primary reasons they were not successful in at least one online course were that the class required too much time (6.2%), a lack of personal motivation (5%), a heavy course load (4.3%), and course difficulty (3%). Fetzner (2013) supported a mandatory online orientation for firsttime online students to address issues such as (a) time management, (b) understanding course requirements, and (c) knowing how to find technical and academic support, which was identified by unsuccessful online students as important information to share with new online students. When asked if they would take another online class in the future, 31.3% of unsuccessful online students said there was no chance at all or that it was not likely. An additional 16.2% responded that it was possible, and 52.5% indicated that they were somewhat or very likely to take another online class (Feztner, 2013). 60 Online instructional strategies that support adult learning theory may contribute to the success of adult online students. Snyder (2009) recommended that online instructors employ several strategies to engage and retain adult students in online classes. First, it is important that instructors establish relationships with students and encourage them to connect with their fellow students. Then, it is important that instructors have effective practices for online instruction such as being consistent and predictable, facilitating communication and collaboration, and accommodating various learning styles. Snyder (2009) also recommended that online instructors encourage a shared responsibility for class leadership, provide accessible and relevant resources, acknowledge student contributions, utilize the internet for information and tools, and allow time for closure and reflection. In addition, Harris and Martin (2012) suggested that colleges and universities focus on faculty development and support in increasing both the amount and variety of instructional technology and multimedia tools used in online classes. A Comparison of Course Delivery Methods Ashby, Sadera, and McNary’s (2011) comparative study of three course delivery formats for intermediate algebra revealed patterns in student enrollment. The study included 167 community college students who selfselected enrollment into a completely live, a blended, or a completely online class. Thirtyfive percent of students enrolled in a live class, 28% enrolled in a blended class, and 38% enrolled in an online class. Students under 20 years of age showed a strong preference for live classes, students 2024 years of age were equally split between the three methods, and students 2549 years of age preferred the online option, comprising 70% of the total online enrollment. Ashby et al. (2011) also noted performance and success patterns across the three delivery methods. Students in the blended class fared the worst with the highest percentage of missing 61 grades, the lowest rate of completion, and a completer pass rate that was higher than the live course, but lower than the online class. Students in the live class had the lowest percentage of missing grades and the highest rate of completion, but also had the lowest completer pass rate of the three methods. The number of missing grades and the completion rates for the online class fell between that
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Title  COLLEGE ALGEBRA COURSE OUTCOMES AMONG NONTRADITIONAL COMMUNITY COLLEGE STUDENTS 
Author  Groce, Jeanetta Dianne 
Subject  Mathematics; Higher education; Adult education 
Abstract  COLLEGE ALGEBRA COURSE OUTCOMES AMONG NONTRADITIONAL COMMUNITY COLLEGE STUDENTS A Dissertation by JEANETTA D. GROCE Submitted to the Office of Graduate Studies of Texas A&M UniversityCommerce in partial fulfillment of the requirements for the degree of DOCTOR OF EDUCATION August 2015 COLLEGE ALGEBRA COURSE OUTCOMES AMONG NONTRADITIONAL COMMUNITY COLLEGE STUDENTS A Dissertation by JEANETTA D. GROCE Approved by: Advisor: Joyce A. Scott Committee: Jon Travis Mark Reid Head of Department: William C. Holt Dean of the College: Timothy Letzring Dean of Graduate Studies: Arlene Horne iii Copyright © 2015 Jeanetta D. Groce iv ABSTRACT COLLEGE ALGEBRA COURSE OUTCOMES AMONG NONTRADITIONAL COMMUNITY COLLEGE STUDENTS Jeanetta D. Groce, EdD Texas A&M UniversityCommerce, 2015 Advisor: Joyce A. Scott, PhD An increasing number of nontraditional students are enrolling in community colleges to achieve their educational and career goals. For many of these students, degree completion is contingent upon the successful completion of college algebra, a course that nearly 50% of enrolled students fail to complete successfully. Nontraditional students, who are more likely to be balancing school, work, and family responsibilities, are often enrolled part time and often rely on the flexibility of online classes. These students are also more likely to be referred to developmental mathematics prior to enrolling in college algebra. The purposes of this study were (a) to examine college algebra course outcomes among adult community college students to determine if differences exist between those who take the class live and those who take it online, (b) to determine if differences exist in college algebra course outcomes based on previous enrollment in developmental mathematics and, (c) to determine if differences exist in college algebra course outcomes based on parttime/fulltime status. v The study participants were community college algebra students age 25 and older. Volunteer participants were recruited from online and live college algebra students enrolled at a large rural community college in North Texas. Informed consent and relevant demographic data were collected through the use of a categorical response questionnaire administered during a 3week period immediately following the midterm exam. Final course grades were provided by the cooperating community college’s mathematics department chairperson at the conclusion of the semester. A chisquare test of independence was used to analyze the data. No statistically significant relationships were identified between college course outcomes and course delivery format, previous enrollment in developmental mathematics, or enrollment status. Findings indicated, however, that a higher percentage of students were successful in the live sections than in the online sections. In addition, participants who had never been enrolled in developmental mathematics passed college algebra at a higher rate than those who had been enrolled in developmental mathematics. Finally, although no statistically significant relationship existed between course outcomes and parttime or fulltime enrollment status, it was noted that parttime students were more likely to enroll in online sections than in live sections. vi ACKNOWLEDGEMENTS First and foremost, I give honor and praise to my Lord and Savior Jesus Christ who has not only saved me, but also carried, strengthened, and blessed me throughout my life. As with other trials in my life, the journey toward the completion of my doctorate has reminded me that, “The LORD is my strength and my defense; He has become my salvation. He is my God, and I will praise him…” (Exodus 15:2). I dedicate this dissertation to Dr. Brenda Reed, who first taught me, at the age of 31, that I was not “math stupid” and that I could, indeed, do math, even algebra. Without you, Dr. Shari Beck, and Dr. Vanessa Huse, none of this would have been possible. I owe a tremendous debt of gratitude to my advisor, Dr. Joyce Scott. Thank you for taking me on halfway through the program and for restoring my faith in the process. Thank you for your continuous support, for your wisdom, and for the hours and hours of editing you did for me. You have been amazing. To Dr. Jon Travis, thank you for making us work so hard in the law class, for doing an independent study so I could stay on track, for agreeing to serve on my committee, and for holding up the standards of the “old guard.” I appreciate that more than you know. To Dr. Katy Denson, I am absolutely certain that God sent you my way when I needed assistance with the statistical processes of this study. I will be eternally grateful for your expertise and your willingness to help. I could not have done this without you. To Dr. Mark Reid, thank you for stepping onto my committee on such short notice and so late in the process. I definitely owe you one. Finally, to my family and friends, thank you, thank you, thank you! You have supported me beyond reason, listened to me complain, encouraged me, and picked up the slack when I was too swamped to do my part. How could I ask for more? vii TABLE OF CONTENTS LIST OF TABLES ...........................................................................................................................x CHAPTER 1. INTRODUCTION ........................................................................................................ 1 Statement of the Problem ....................................................................................... 7 Purpose of the Study .............................................................................................. 7 Research Questions ................................................................................................ 8 Hypotheses ............................................................................................................. 8 Significance of the Study ....................................................................................... 9 Method of Procedure............................................................................................ 16 Institution Board Approval ...................................................................... 16 Design of Study........................................................................................ 17 Selection and Development of Instruments ............................................. 18 Selection of Sample ................................................................................. 18 Collection of Data .................................................................................... 19 Treatment of the Data .............................................................................. 20 Definitions of Terms ..............................................................................................20 Limitations .............................................................................................................23 Delimitations ..........................................................................................................23 Assumptions ...........................................................................................................24 Organization of Dissertation Chapters ...................................................................24 viii CHAPTER 2. REVIEW OF THE LITERATURE ...............................................................................25 Nontraditional Students .........................................................................................25 Developmental Education ......................................................................................35 College Algebra .....................................................................................................47 Online Classes ........................................................................................................54 Conclusion .............................................................................................................64 3. METHOD OF PROCEDURE........................................................................................65 Research Questions ................................................................................................65 Hypotheses .............................................................................................................66 Design of Study......................................................................................................66 Description of Instruments .....................................................................................68 Collection of Data ..................................................................................................69 Treatment of Data ..................................................................................................70 Summary ................................................................................................................73 4. PRESENTATION OF FINDINGS ................................................................................74 Research Questions ................................................................................................74 Hypotheses .............................................................................................................75 Data Collection ......................................................................................................75 Results ....................................................................................................................76 Summary ................................................................................................................82 ix CHAPTER 5. SUMMARY OF FINDINGS, IMPLICATIONS, CONCLUSIONS, AND RECOMMENDAIONS FOR FUTURE RESEARCH..................................................83 Summary of the Study ...........................................................................................84 Findings..................................................................................................................85 Conclusions ............................................................................................................89 Implications............................................................................................................90 Recommendations for Future Research .................................................................91 Summary ................................................................................................................91 REFERENCES ............................................................................................................................ 93 APENDICES...............................................................................................................................106 Appendix A. Student Invitation Email ...................................................................................107 B. Student Invitation ..............................................................................................109 C. Informed Consent Form ....................................................................................111 D. Questionnaire ....................................................................................................114 VITA ...........................................................................................................................................116 x LIST OF TABLES TABLE 1. Cross Tabulation of Course Outcome and Course Type ....................................................77 2. Cross Tabulation of Course Outcome and Developmental Mathematics Status ................79 3. Cross Tabulation of Course Type and Developmental Mathematics Status ......................80 4. Cross Tabulation of Course Type and Enrollment Status ..................................................82 1 Chapter 1 INTRODUCTION According to the Organisation for Economic Cooperation and Development (OECD), “Governments are increasingly looking to international comparisons of education opportunities and outcomes as they develop policies to enhance individuals’ social and economic prospects, provide incentives for greater efficiency in schooling, and help to mobilise resources to meet rising demands” (2014, p. 3). Higher levels of educational attainment have been associated with benefits for both individuals and societies around the world. Completing a tertiary program, typically referred to in the United States as a 2year, 4year, or graduate program, has been associated with better health, increased career opportunities, and higher earnings for individuals. Consequently, societies benefit from higher proportions of tertiaryeducated citizens through higher employment rates, reduced welfare expenditures, and increased tax revenue. Considering lost income and public grants, the public recovers four times the cost associated with providing a man with a tertiary education and two and a half times the cost of educating a woman to the same level (OECD, 2014). In OECD countries, employment rates remained consistently higher among tertiaryeducated adults from 20072012. In 2012, 80% of OECD tertiaryeducated adults between the ages of 25 and 64, compared to 70% of adults with a secondary credential, were employed. Older tertiaryeducated adults were slightly more likely to be employed than were younger adults with the same level of education. (OECD, 2014). The OECD associated greater educational achievement with increased lifetime income but found a particularly large increase among the more educated older adults. The organization maintained that, “People with higher levels of 2 education are more likely to be employed, and remain employed, and have more opportunities to gain experience on the job” (OECD, 2014, p. 134). The percentages of tertiaryeducated adults increased by 10% across all OECD countries between 2000 and 2012, with approximately 34% of women and 31% of men completing a college degree (OECD, 2014). Much of the growth has been attributed to an increase in the number of younger adults who completed degrees, but the average age at which students earned a university degree varied in 2012. Across all OECD countries, students completed a university degree at approximately 27 years of age. In Belgium, Luxemburg, Mexico, the Netherlands, and the United Kingdom, students earned the degree approximately 2 years earlier, at 25 years of age. Students in Brazil, Finland, Sweden, Iceland, and Israel tended to complete a university degree at the older age of 29 (OECD, 2014). The percentage of parttime students also varied. Of tertiary students in all OECD countries, 21% were enrolled part time in 2012. In Argentina, Finland, Hungary, New Zealand, the Slovak Republic, Spain, and the United States, the percentage of parttime students was 30%, significantly higher than the global average (OECD, 2014). Approximately 10% of adults in OECD countries participated in some formal education in 2012. The percentages were above average in AngloSaxon countries (including the United States), Nordic countries, the Netherlands, and Spain. In contrast, France, Japan, and Korea had below average adult enrollment with less than 5% of adults participating in formal education (OECD, 2014, p. 396). According to the OECD (2014), the proportion of adults in education programs may be reflective of the flexibility required by older students. Across all OECD countries, 45% of adults who indicated a desire, but inability, to participate in learning activities during the preceding year, specified work and family responsibilities as the reason why they 3 were unable to participate. An additional 14% asserted that cost was a factor, 12% indicated that the desired program was not available at a convenient time or location, 8% referred to a “lack of employer support,” 4% indicated that unexpected events or circumstances prevented them from attending, and 3% stated that they did not have the prerequisites (OECD, 2014, p. 395). Governments around the world have introduced programs to encourage degree completion among older adults who may be unable to earn a credential in the expected timeframe due to the need to balance work and study requirements (OECD, 2014). Although extending the time to completion increases the cost of adult degree acquisition, adults may be more certain of their chosen major and may be more motivated to complete the degree. As stated by the OECD, It is crucial to provide, and ensure access to, organised learning opportunities for adults beyond their initial formal education, especially for workers who need to adapt to changes throughout their careers. The relevance of continued learning opportunities now extends to workers in both high and lowskilled occupations. (2014, p. 390) Information supplied by the U.S. Census Bureau and the U.S. Department of Labor (see below) supported the need to ensure access to higher education among nontraditional students in the United States, as well. According to the U.S. Census Bureau, American FactFinder (2013), over 52% of Americans were between the ages of 25 and 64 in 2013, and the median age of the total population was 37.5 years. Only 10% of the American population was between the ages 18 and 24, the ages typically associated with college attendance, yet 31.1% of American females and 25.4% of American males age three and older were enrolled in college or graduate school in 2013. In the same year, nearly 60% of Americans age 16 and over were employed (U.S. Census 4 Bureau, American FactFinder, 2013). These numbers suggest significant college enrollment among working American adults over the age of 24. In the United States, college enrollment increased by 32% between 2001 and 2011 (Snyder & Dillow, 2013). Enrollment increases were not equal across age groups, however. During this time, enrollment among students under 25 increased by 35%, while enrollment among students 25 or older increased by 41%. Although the difference in enrollment increases between the two age groups is expected to narrow between 2011 and 2021, enrollment among older students is expected to remain slightly higher than that of younger students (Snyder & Dillow, 2013). The average time to degree completion varies widely in the United States. In 2008, the median time in which students completed a bachelor’s degree was 52 months (Cataldi et al., 2011). During that year, 44% of all graduates completed a bachelor’s degree in 48 months, 23% completed in 4960 months, and 9% completed the degree in 6172 months. Students who began their postsecondary education at 4year institutions graduated in less time than students who began at 2year institutions. Students who first attended 4year institutions earned a bachelor’s degree in approximately 47 months, compared to 63 months for those who first attended 2year institutions. A significant difference in completion times was also found between students who attended college immediately after high school and those who did not. Students who started college within one year of high school graduation earned a bachelor’s degree in about 51 months, compared to approximately 80 months for those who delayed enrollment (Cataldi et al., 2011). In 2014, U.S. Department of Labor, Bureau of Labor Statistics (BLS) found that educational attainment was associated with higher employment rates for American adults 25 and older. In 20102011, 22% of U.S. workers 25 and older had some college, but no degree. An 5 additional 9% had an associate’s degree, and 21.6% had a bachelor’s degree as the highest level of educational attainment. In 2013, unemployment rates were 7.5% for those with only a high school diploma; 7.0% for those with some college, but no degree; 5.4% for those with an associate’s degree, and 4.0% for those with a bachelor’s degree. People with bachelor’s degrees were also found to be less affected by rising unemployment rates between 2008 and 2010 than were those without bachelor’s degrees (Kena et al., 2014). The U.S. Department of Labor, BLS, found that, “Occupations that typically require postsecondary education for entry have higher wages” (2013a, p. 6). Among adults who were at least 25 years old and employed fulltime in 2013, the average weekly income was $651 a week for those with only a high school diploma; $727 for those with some college, but no degree; $777 for those with an associate’s degree; and $1,108 for those with a bachelor’s degree (U.S. Department of Labor, BLS, 2014). According to the data, adults with bachelor’s degrees earned an average of $457 per week more than those with only a high school diploma and $381 per week more than adults who began college but did not earn a degree. This difference in average earned income is especially relevant when one considers that 15.8% of all Americans and 22.2% of American children lived in poverty in 2013 (U.S. Census Bureau, American FactFinder, 2013). In 2012, approximately onethird of all U.S. entrylevel jobs required at least some postsecondary education (U.S. Department of Labor, BLS, 2013a). Between 2012 and 2022, some 108,882,000 new and replacement jobs are expected to require either an associate’s or bachelor’s degree (U.S. Department of Labor, BLS, 2013b). In 2013, however, slightly less than 30% of American adults 25 and older had some college or an associate’s degree, and only 18.4% had a bachelor’s degree (U.S. Census Bureau, American FactFinder, 2013). 6 While the data support the financial benefits of completing a college degree, adult students have complex lives and varied reasons for enrolling in college. Adults may enroll or reenroll in college to create additional career opportunities, create a better life, or grow intellectually. Kasworm (2008) noted, however, that when adults assume the role of student, the new responsibility does not replace or diminish existing obligations, but is added to them. The challenges and complexities associated with balancing these roles and creating more opportunities may simultaneously bolster and challenge adult students’ sense of self. Kasworm also stated that adult students “believe they have a high probability of success and are committed to quality learning experiences and a collegiate credential” (2008, p. 28). “While adult students are often more motivated and more determined to overcome their unique obstacles than traditionalage students, mathematics courses prove to be barriers to adult student graduation” (Tennant, 2014, p. 17). Students 25 and older typically scored significantly lower on math placement tests than traditional students and were more likely to be placed into developmental mathematics classes (Calcagno, Crosta, Bailey, & Jenkins, 2007b; Tennant, 2014). Studies examining the effects of developmental mathematics on nontraditional student completion rates have produced mixed results. Being underprepared for collegelevel mathematics has been identified as a significant dropout risk factor for all students (Tennant, 2014). However, Calcagno et al. (2007a, 2007b) found that, when controlling for math ability, nontraditional students were more likely to graduate than their younger counterparts. Tennant (2014), however, found that, although nontraditional students who were prepared for collegelevel mathematics had graduation rates similar to younger students who were prepared for collegelevel math, the rates were dissimilar among those students who were not prepared. According to Tennant (2014), nontraditional students who began in developmental mathematics 7 classes were less likely or much less likely to graduate than were younger students who began in developmental mathematics classes. Statement of the Problem High failure rates in college algebra may prove to be a barrier to degree completion for adult students who may have had little exposure to formal mathematics instruction for an extended period of time (Hardin, 2008; Thiel, Peterman, & Brown, 2008). Developmental education, which accounted for $206 million of the 20062007 Texas biennial budget (Pretlow & Wathington, 2012), may actually serve as an additional barrier rather than as a benefit for college completion (Charles A. Dana Center, Complete College America, Inc., Education Commission of the States, & Jobs for the Future, 2012). The problem may be compounded by a change in course delivery modes as more nontraditional students enroll in online classes. The goal of this study was to explore the possible relationship between course delivery format, previous enrollment in developmental mathematics, and college algebra course outcomes for adult students. Purpose of the Study The primary purpose of this study was to examine college algebra course outcomes among adult community college students to determine if differences exist between those enrolled in live and online college algebra classes. Additional purposes were to determine if differences exist in college algebra course outcomes based on previous enrollment in developmental mathematics and parttime/fulltime status. 8 Research Questions The following research questions guided the study: 1. Does a statistically significant relationship exist between college algebra course outcomes and online or live enrollment among adult community college students? 2. Does a statistically significant relationship exist between college algebra course outcomes and previous enrollment in developmental mathematics among adult community college students? 3. Does a statistically significant relationship exist between college algebra course outcomes and course type (online or live) with previous enrollment in developmental mathematics among adult community college students? 4. Does a statistically significant relationship exist between college algebra course outcomes and course type (online or live) with enrollment status (parttime or fulltime) among adult community college students? Hypotheses The following null hypotheses were tested at the .05 level of significance: 1. No significant relationship exists between college algebra course outcomes and online or live enrollment among adult community college students. 2. No significant relationship exists between college algebra course outcomes and previous enrollment in developmental mathematics among adult community college students. 3. No significant relationship exists between college algebra course outcomes and course type (online or live) with previous enrollment in developmental mathematics among adult community college students. 9 4. No significant relationship exists between college algebra course outcomes and course type (online or live) with enrollment status (parttime or fulltime) among adult community college students. Significance of the Study Postsecondary education is a factor in employment trends. While national unemployment rates increased across all education levels between 2008 and 2010, and subsequently dropped between 2010 and 2013, unemployment levels remained lowest among people who held a bachelor’s degree or higher (Kena et al., 2014). Carnevale, Smith, and Strohl (2010) predicted a similar pattern for Texas. The number of new Texas jobs requiring at least some postsecondary education is expected to increase by 1.3 million between 2008 and 2018, with an estimated 56% of all Texas jobs projected to demand at least some college by 2018. Complete College America (2013) found that many students are not completing their degrees within expected timeframes, however. An analysis of the 20092010 graduation rates indicated that fewer than 30% of Texas college students graduated on time, within 2 years for an associate’s degree or within 4 years for a baccalaureate degree. On average, fulltime Texas students completed an associate’s degree in 4.7 years and a bachelor’s degree in 5.3 years. Parttime students completed an associate’s degree in an average of 5.2 years and a bachelor’s degree in an average of 6 years (Complete College America, 2013). In 2011, students 25 years of age and older accounted for 29% of the fulltime and 48% of the parttime enrollment at public 2year institutions in the United States (Kena et al., 2014). In the same year, 50% of all Texas college students were enrolled part time, and data indicated that less than 25% of parttime Texas students completed an associate’s degree within 6 years (Complete College America, 2013). In the fall of 2013, some 73% of all Texas community 10 college students were enrolled part time (THECB, 2014a). These growth trends are expected to continue. Kena et al. (2014) projected that enrollment in public 2year institutions will increase by 16% and parttime undergraduate enrollment will increase by 17% in the United States from 2012 to 2023. While college enrollment is expected to increase, attrition has continued to plague higher education. Between the 20042005 and 20082009 academic years, one fifth of all U.S. firsttime, fulltime community college students dropped out prior to their second year of college (Schneider & Yin, 2011). In the 20082009 academic year alone, American taxpayers spent $1 billion on firsttime fulltime college students who did not return for their second year. In the same year, Texas ranked second in the nation in the amount of expenditures for firstyear community college students who later withdrew before completing a program or degree. Between 2004 and 2009, Texas residents spent $360 million dollars in expenditures on firsttime community college students who quit prior to their second year of college (Schneider & Yin, 2011). In the fall of 2011, nearly 35% of the instate students enrolled in Texas public 2year institutions were at least 25 years of age. Factors such as a poor economy, global outsourcing, increasing technology, and a need for new job skills have contributed to increased enrollment among students 25 years of age and older, also referred to as nontraditional students (Jesnek, 2012). College enrollment among adults aged 50 and older has also increased as older adults have increasingly sought new employment opportunities beyond the traditional retirement age (Vacarr, 2014). If enrollment trends follow projected population patterns, the percentage of nontraditional students may continue to increase over time. The percentage of adults older than traditional 11 college age is expected to continue to rise in Texas and across the United States. By the year 2020, slightly over half of the Texas population is expected to be at least 35 years of age, representing a 2% increase over 2012 (THECB, 2013b). The U.S. Census Bureau (2010) projected that the number of adults aged 55 and older will increase by 36 million between 2014 and 2030. Vacarr (2014) summarized the growing population of older students and recognized the challenges they face by stating that: At a time when traditional “retirement” increasingly marks the beginning of a new phase of work (whether by choice, necessity, or some combination of the two), millions will need help if they are to make a successful transition. Looking toward another two, three, or even four decades of healthy active life, many people are eager to gain new skills and the credentials that will help them move into a new worklife chapter. Like students of traditional college age, they will also need help navigating what is fast being recognized as one of life’s major transitions, akin to adolescence in its significance. Here we have the makings of a winwin scenario. Colleges need students, and a growing underserved population needs supportive educational pathways into a new life chapter, precisely what colleges have historically provided. (p. A 52) Nontraditional students are more likely to attend college part time and often take longer to graduate than traditional students (Calcagno et al., 2007a; Newbold, Mehta, & Forbus, 2010; Tinto, 2012). Tinto (2012) noted that parttime students have many obligations and therefore go to campus only to attend class. Tinto further maintained that, for parttime students, college success depends on success in the classroom. 12 In addition to dealing with demands outside of the classroom, nontraditional students may “experience academic difficulties because they have been away from an academic setting for an extended time” (Hardin, 2008, p. 54). Adult learning is simultaneously physical, cognitive, and emotional; and adult students may experience anxiety, fear, and excitement upon returning to school (Willans & Seary, 2011). Further, nontraditional students are more likely than their younger counterparts to begin college lacking the computer proficiency necessary to succeed in most college courses (Jesnek, 2012). All of these factors may affect student success. McGrath (2009) asserted that andragogy “aims to look at how learning in the classroom can be made more attractive for adult students” (p. 109). Andragogy, a theory of adult learning founded primarily by Malcolm Knowles, developed over a period of 50 years and has been defined as “the art and science of helping adults learn” (Knowles, Holton, & Swanson, 2011, location 1155). Rooted in humanism and pragmatism, andragogy has been described as an “individualtransactional model of adult learning.” Unlike pedagogy, which is focused on covering specific content and organizing materials and lessons into manageable units, andragogy is focused on the learning process. Adult motivation continues to be an important factor in adult learning. Rodrigues asserted that, “Learners see education as a process for achieving their full potential in life” (2012, p. 31). Knowles et al. (2011) asserted that adults are primarily motivated by internal issues such as the desire for professional growth, a better quality of life, and higher selfesteem. Knowles et al. (2011) additionally noted that adults are motivated by personal goals, interest, and by clearly stated learning objectives. The Charles A. Dana Center et al. (2012) found that developmental instruction, intended to prepare students for entrylevel courses, may actually serve as a barrier to degree completion. 13 Despite the fact that 70% of all U.S. community college students enroll in at least one developmental course, 72% to 80% of those students fail to register for the subsequent entrylevel course (Bahr, 2010; Charles A. Dana Center et al., 2012; Templin, 2011; Wolfle, 2012). These numbers support findings that approximately 75% of community college students who enroll in developmental classes fail to earn a degree or to transfer to another institution within 8 years (Charles A. Dana Center et al., 2012; Parker, 2012). Bonham and Boylan (2012) stated that, “Developmental mathematics as a barrier to educational opportunity represents a serious concern for the students as well as higher education policy makers” (p. 14). Older students are significantly more likely than traditionally aged students to be assigned to the very beginning stages of the developmental mathematics sequence (Complete College America, 2012; Walker & Plata, 2000). This finding is concerning, as studies indicated a strong negative correlation between enrollment in the lower levels of developmental mathematics and subsequent success in college algebra (Doyen, 2012; Donovan & Wheland, 2008). While Fike and Fike found that “students successful in the developmental course ‘catch up’ with their collegeready peers” (2012, p. 8), only 13% of nontraditional community college freshmen who enroll in a developmental course ever complete the associated entrylevel course (Complete College America, 2012). College algebra, a requirement for most undergraduate degrees, may block degree completion. Every year, nearly half of the 1,000,000 U.S. college algebra students fail to pass the class (Herriott & Dunbar, 2009). Studies investigating a possible correlation between student age and success in college algebra have produced inconsistent results. Penny and White (1998) and Wolfle (2012) identified a weak positive correlation between student age and success in college algebra. On the other hand, studies investigating a relationship between student age, 14 previous enrollment in developmental mathematics, and success in college algebra produced different results. Doyen (2012) found that among students who had completed intermediate algebra within the previous calendar year, students 25 and older succeeded in college algebra at a slightly higher rate than did traditional students. Conversely, Calcagno et al. (2007b) found that nontraditional students who had taken developmental mathematics were less successful in college algebra than were traditional age students. In the United States, enrollment in online classes increased considerably faster than the overall student enrollment between 2002 and 2012. While the overall U.S. higher education enrollment grew at a rate of 2.5% annually, the annual compound growth rate of U.S. online enrollment reached 16.1% during this period. In the fall of 2012, online enrollment accounted for approximately one third of all enrollments in U.S. public degreegranting institutions (Allen & Seaman, 2014). Distance education, including online enrollment, has also grown in Texas. In fall 2000, distance education accounted for 15.3% of all attempted semester credit hours at Texas public community and technical colleges. By spring 2014 this percentage had increased to 35.4% (THECB, 2014b). Older students register for online classes at higher rates than younger students (Harris & Martin, 2012; Wilson & Allen, 2011). Although students 25 and older may actually prefer live classes, they often register for online classes due to accessibility and convenience (Beaghan, 2013). Students in Harris and Martin’s (2012) study identified flexibility in assignment completion, distance from campus, and the ability to attend school while still fulfilling family and jobrelated responsibilities as the primary factors motivating online enrollment. Once enrolled in online courses, motivation to continue is an important factor for adult students. Rodrigues (2012) found that nontraditional students were motivated to continue the 15 online learning process through continuous feedback and positive reinforcement. McGrath (2009) asserted that nontraditional students’ motivation to remain and participate in the online learning environment may also be increased through participation in collaborative small groups and increased perceptions of belonging. Online adult instructors in one study indicated a strong belief that participating in a carefully designed educational environment could be highly motivating to adult students if content learning occurred in a way that also improved selfesteem and encouraged a feeling of achievement (Wang & KaniaGosche, 2011). It is interesting to note that the ability to share both personal and academic experiences was found to be important to adult learners. Allen and Seaman (2014) reported that 45% of public U.S. higher education institutions found attrition to be a bigger problem in online than in faceface classes, however. This finding is consistent with Pontes and Pontes’ (2012) conclusion that distance education students were significantly more likely to drop out or to experience an enrollment gap than live students. Fetzner (2013) found that 47% of students who were unsuccessful in at least one online class attributed their failure to falling behind in class and not being able to complete all of the missed assignments, to dealing with personal problems such as child care and health concerns, and to being unable to balance school, work, and family responsibilities. Tinto (2012) stated, “In admitting a student, a college enters into a contract—indeed, takes a moral obligation—to establish those conditions on campus, especially in the classroom, that enhance the likelihood that students who are willing to expend the effort will succeed” (p. 120). Rodrigues (2012) noted that although many adults do not have a strong mathematical knowledge base, their commitment to attend and to participate in class indicates a readiness to learn. College algebra continues to serve as a roadblock to degree completion, especially for 16 nontraditional students who often enroll in college classes lacking the necessary technology and mathematics skills. Leaders in higher education need to take into account this deficit among nontraditional students and to conduct further research in two areas: to determine if a difference exists in course outcomes among nontraditional students enrolled in online versus live college algebra classes, and to ascertain if prior enrollment in developmental mathematics classes is a predictor of success or failure in either or both formats. The results of such research may allow colleges and universities to serve better the unique needs of nontraditional students, thus improving outcomes for students and institutions of higher education and preparing more graduates for the workforce of the future. Method of Procedure The purpose of this study was to examine the college algebra course outcomes among adult community college students. The assessment was accomplished by determining if any significant differences exist in course outcomes for students based on course type, previous enrollment in developmental mathematics, and fulltime or parttime enrollment status. The procedures used include the (a) Institutional Review Board Approval, (b) Design of the Study, (c) Selection and Development of Instruments, (d) Selection of Participants, (e) Collection of Data, and (f) Treatment of Data. Institutional Review Board Approval The researcher completed the Collaborative Institutional Training Initiative online Protection of Human Subjects Course, the Social and Behavioral Responsible Conduct of Research Course, and Conflict of Interest Course as a requirement to conduct research. Permission to conduct this study was granted by the Texas A&M UniversityCommerce Institutional Review Board (IRB). Permission to conduct this study at the participating 17 community college was received from the college’s Office of Institutional Research and Outreach. Design of the Study This study was ex post facto because the researcher was “unable to cause a variable to occur by creating a treatment and must examine the effects of a naturalistically occurring treatment after it has occurred” and because the researcher sought to “relate this afterthefact treatment to an outcome or dependent measure” (Tuckman & Harper, 2012, p. 172). This study followed a causalcomparative design as the researcher was “contrasting the characteristics of state with those of its opposite” (Tuckman & Harper, 2012, p. 182). This quantitative study used the chisquare test to determine if relationships existed between college algebra course outcome and several groups of nontraditional students. All variables were categorical, with two levels each. When categorical data are collected, the number or frequency that fall into each category are analyzed (Field, 2013). The dependent variable, course outcome, was categorical with two possible outcomes of pass or fail. Other categorical variables, thought of as the independent variables, were the type of class (live or online), previous enrollment in developmental mathematics (yes or no), and enrollment status (fulltime or parttime). A literature review revealed the significance of including the independent variables in the study (Allen & Seaman, 2014; Bahr, 2010; Calcagno et al, 2007a; Calcagno et al, 2007b; Charles A. Dana Center et al., 2012; Complete College America, 2013; Fetzner, 2013; Ghaffari, 2011; Parker, 2012; Pretlow & Wathington, 2012; Wolfle, 2012). A categorical response questionnaire solicited student age, type of class, previous enrollment in developmental mathematics, and enrollment status (Tuckman & Harper, 2012). The dependent variable was the course outcome of pass or fail. The literature revealed the significance of the dependent variables in the study (CarneyCrompton, & 18 Tan, 2002; Doyen, 2012; Penny & White, 1998; Pontes & Pontes, 2012). Final course outcomes were collected from the institution participating in the study at the conclusion of the semester. Selection and Development of Instruments The categorical response questionnaire used to collect data for the study was fashioned from an examination of the literature (Allen & Seaman, 2014; Bahr, 2010; Calcagno, Coast, Bailey, & Jenkins, 2007a; Calcagno, Coast, Bailey, & Jenkins, 2007b; Charles A. Dana Center et al., 2012; Complete College America, 2013; Fetzner, 2013; Ghaffari, 2011; Parker, 2012; Pretlow & Wathington, 2012; Wolfle, 2012). The questionnaire had four categorical response questions designed to gather data regarding student age, type of class (online or live), previous enrollment in developmental mathematics (yes or no), and enrollment status (fulltime or parttime). The questionnaire was reviewed for validity by the researcher’s advisor and an additional faculty member from the Department of Educational Leadership. The questionnaire was also reviewed by the mathematics department chairperson at the cooperating Texas community college. All suggested revisions were completed before the questionnaire was distributed to study participants. To establish reliability, the questionnaire was pilottested by a sample of community college algebra students. One area of weakness related to the renumbering of developmental mathematics classes was noted and corrected for clarity (Tuckman & Harper, 2012). Students who participated in the pilottesting were not included in the study sample. Selection of Sample Quantitative research allows for convenience sampling for the purpose of making generalizations about the target population (Creswell, 2005). For this quantitative study, the target population was community college students, aged 25 and older, who were enrolled in 19 online or live college algebra classes in spring 2015. A sample from the target population consisted of students 25 and older who were enrolled in online and live college algebra classes at four campuses of a large rural community college in North Texas. Students age 25 and older accounted for approximately 28% of the entire enrollment at the selected community college. Participation in the study was voluntary. All college algebra students, including those who were enrolled in an online class, were required to take a live midterm exam. Initial recruiting of potential participants occurred when they went to campus to take the midterm exam. The researcher then visited live sections of the course to recruit additional volunteer participants. An informed consent form and brief categorical response questionnaire were distributed to students. Using the student questionnaire, participants provided their name, age, fulltime or parttime enrollment status, current enrollment in an online or live algebra class, and previous enrollment in developmental mathematics classes (Tuckman & Harper, 2012). Students who denied consent returned the unsigned form or disposed of it themselves. Students who volunteered to participate in the study returned a signed consent form and a completed questionnaire to the faculty test administrator, their instructor, or the researcher. All documents were securely stored in a locked filing cabinet. Volunteers who were at least 25 years old and were currently enrolled in a college algebra class at the institution were included in the study. Collection of Data The initial data collection tool (Tuckman & Harper, 2012) was a categorical response questionnaire soliciting volunteer participants’ (a) name, (b) age, (c) enrollment status (fulltime/parttime), (d) enrollment in an online or live class, (e) previous enrollment in developmental mathematics (yes/no), and (f) consent to access the final college algebra grade. All informed consent and questionnaire data were collected within the 3 weeks following the 20 midterm exam. At the end of the semester, after posting of final grades, the researcher obtained participants’ final course grades from the cooperating mathematics department chairperson. Treatment of Data All four research questions were answered using a chisquare test for independence. This test “compares the observed frequencies or proportions of cases that occur in each of the categories with the values that would be expected if there was no association between the two variables being measured” (Pallant, 2010, p. 217). For Research Question 1, the independent variable was type of class, live or online. For Research Question 2, the independent variable was previous enrollment in developmental math status (yes or no). To answer Research Question 3, a variable representing four groups was computed: (a) those in a live class who previously had developmental mathematics, (b) those in a live class who did not previously have developmental mathematics, (c) those in an online class who previously had developmental mathematics, and (d) those in an online class who did not previously have developmental mathematics. This became the independent variable delineating type of class and developmental mathematics status. To answer Research Question 4, another variable was computed to be the independent variable delineating type of class and fulltime/parttime status: (a) fulltime students enrolled in a live class, (b) parttime students enrolled in a live class, (c) fulltime students enrolled in an online class, and (d) parttime students enrolled in an online class. Definitions of Terms The following terms are defined as they were used in the study: Blended or hybrid course. Allen and Seaman (2010) defined a blended or hybrid course as a “course that blends online and live delivery” (p. 5). In an online or blended class, a significant amount of the instruction is delivered online, and fewer live meetings are required 21 than are required for a live class. The Texas Higher Education Coordinating Board (THECB) defined a blended or hybrid course as a course in which between 50% and 85% “of the planned instruction occurs when the students and instructor(s) are not in the same place” (2012, p. 37). Community college. Cohen and Brawer (2008) defined a community college as “any institution regionally accredited to award the associate in arts or the associate in science as its highest degree” (p. 5). Developmental education. Developmental education includes “precollege, nondegree credit courses, interventions, tutorials, laboratories, and other means of assistance that are included in a plan to ensure the success of a student in performing entrylevel academic coursework” (Texas Administrative Code Title 19, Part 1, Ch. 4, Subch C. Rule §4.53). Distance education. The THECB (2012) defined distance education as “the formal educational process that occurs when the students and instructors are not in the same physical setting for the majority (more than 50 percent) of instruction” (p. 25). Distance education course. According to the THECB (2012), a distance education course is one in which the instructor and the students are not in the same location for more than half of the instruction. Distance education courses may be offered in a synchronous or asynchronous format to one or more locations, including the main campus, through “electronic, correspondence, or other means” (p. 25). Enrollment gap. An enrollment gap occurs when a student is enrolled for only part of an academic year (Pontes & Pontes, 2012). Live course. Live courses include traditional and webenhanced classes in which most of the instruction is delivered in person. According to Allen and Seaman (2010), up to 29% of the instruction in a live course may be delivered online. 22 Fulltime student. An undergraduate student enrolled in 12 or more semester credit hours in a fulllength semester is considered to be a fulltime student (THECB, 2012). Nontraditional student. Horn and Carroll (1996) indicated that age, particularly for students over 24 years old, “has become the defining characteristic for this population” (p. 3). The researchers also determined that age “acts as a surrogate variable that captures a large, heterogeneous population of adult students who often have family and work responsibilities as well as other life circumstances that can interfere with successful completion of educational objectives” (Horn & Carroll, 1996, p. 3). For the purposes of the current study, unless otherwise noted, a nontraditional student was defined as any student who was at least 25 years old. Online course. An online course is a class in which at least 80% of the content is delivered online. Online classes typically do not include any live meetings (Allen & Seaman, 2010). Parttime student. An undergraduate student enrolled in less than 12 semester credit hours in a fulllength semester is considered to be a parttime student (THECB, 2012). Semester credit hours (SCH). According to the THECB (2012), a semester credit hour is “a unit of measure representing an hour (50 minutes) of instruction over a 15week period in a semester or a trimester system or a 10week period in a quarter system” (p. 54). Texas education code. The Texas education code is the set of Texas state statutes regarding education (THECB, 2012). Texas Success Initiative. The Texas Success Initiative (TSI) is a legislatively mandated program that provides Texas public colleges and universities with flexibility in determining the college readiness of entering students. The TSI requires that students be tested in reading, writing, and mathematics skills and be provided with “appropriate counseling, advice, and 23 opportunities—such as developmental education courses or noncoursebased education” to improve college readiness skills if necessary (THECB, 2012, p. 63). TSI Assessment. The TSI Assessment is a program used by Texas public colleges and universities to assess the reading, writing, and mathematics skills of entering college students to determine individual preparation to begin freshmenlevel coursework (THECB, 2013c). Limitations This study was bound by the following limitation: 1. Participants selfreported certain data, including age, previous enrollment in developmental courses, enrollment in an online or live college algebra class, and parttime or fulltime enrollment status. Delimitations The following delimitations were applied to this study: 1. Participants were recruited from four campuses of one large community college in Texas. 2. The study included students age 25 and older who were enrolled in fully online and live college algebra classes; this study did not include students enrolled in hybrid college algebra classes. 3. The study included only those college algebra students who were enrolled in full semester, 16week college algebra classes. The study did not include students who were enrolled in 6week or 8week courses. 4. The study did not consider participants’ race, gender, socioeconomic status, or previous experience. 24 5. The study did not consider faculty status or preparation, such as fulltime or parttime status, level of degree attainment, experience, or training. Assumptions This study was conducted with the following assumptions: 1. The pilot study of the questionnaire ensured reliability and validity. 2. Participants responded to questionnaire items honestly and accurately. Organization of Dissertation Chapters The research study is organized in five chapters. Chapter 1 includes an introduction, problem statement, purpose of the study, research questions, hypotheses, significance of the study, method of procedure, definitions of terms, limitations, delimitations, and assumptions. Chapter 2 consists of an extensive review of the related literature, including the characteristics of nontraditional students, the prevalence and effectiveness of developmental education, the commonality of required college algebra, and the growth and perceptions of online college courses. Chapter 3 provides a detailed explanation of the method of procedure, and Chapter 4 includes a presentation and analysis of research findings. Chapter 5 contains a summary of the study, a discussion of the findings, conclusions, implications, and recommendations for future research. 25 Chapter 2 LITERATURE REVIEW The United States is shifting from a focus on college accessibility to outcomebased funding in an attempt to increase graduation rates (Bradley, 2012). At the same time, nontraditional students are enrolling in college at growing rates, increasing from 30% of the total undergraduate population in 1996 to 50% in 2006 (CarneyCrompton & Tan, 2002; Newbold, et al., 2010). The surge of online classes and degree programs has provided nontraditional students with access to a college education by removing scheduling and transportation obstacles. Developmental mathematics and college algebra classes, which have high failure rates, may prove to be a roadblock for nontraditional students who may have had little exposure to formal mathematics instruction for an extended period. The purpose of this literature review is to examine the related literature and lay a foundation for further research in this area. Nontraditional Students Characteristics of Nontraditional Students Students are generally referred to as adult or nontraditional if they are older than traditional college students and have not moved directly from high school into college. Nontraditional students are generally over the age of 24 and are more likely to have a spouse or livein partner and to be commuting more than five miles to school (Newbold, et al., 2010). Compton, Cox, and Laanan (2006) asserted that adult students often enroll in postsecondary education after a change in economic, employment, or marital status and are more likely than younger students to: pursue a specific vocational certification or degree; have a specific purpose, often related to career advancement, for attending college; 26 consider themselves to be an employee, spouse, or parent over being a student; enroll in distance education as a way to incorporate school into an already busy life; speak languages other than English; and leave college without a degree. (p. 74) According to Horn, Cataldi, and Sikara, “students who delay their postsecondary enrollment a year or more after high school differ fundamentally from those who enroll immediately” (2005, p. 33). In describing students who delay college enrollment, Horn, Cataldi, and Sikara maintained that Students who delay their postsecondary enrollment may do so for numerous reasons. Some may not be academically prepared to attend or have the financial resources necessary to enroll. Others may serve in the military, find employment, or start a family before enrolling. Students who delay enrollment for a long period of time are likely to enroll to advance in or change their careers. For whatever reasons students wait to enroll in college, those who do delay are at considerable risk of not completing a postsecondary credential when compared with their peers who enroll immediately after high school graduation. (2005, p. iii) Motivation and Confidence of Nontraditional Students Motivation is an important factor for all students, including adult learners. Shillingford and Karlin, (2013) found that while both intrinsic and extrinsic motivation affect nontraditional students’ motivation for learning, nontraditional students tend to be more intrinsically motivated than traditional students, meaning that they are more likely to engage in learning activities because it increases their feelings of competence and selfdetermination. Similarly, Swain and Hammond (2011) noted that nontraditional students’ motivation is strongly associated with their 27 sense of self, both the person they are now and the person they will become, and may be influenced by their desire to reinvent themselves or demonstrate their intellectual competence. Jinkens (2003) noted that nontraditional students may be very motivated to continue their studies by family obligations and employment factors, the circumstances that actually limit the amount of time they can devote to the endeavor. Jinkens also maintained that nontraditional students may be more committed to completing their studies than traditional students, even though they are often making more sacrifices as a result of that commitment. A faculty participant in Jinkens’ study alluded to this idea in the following quote, My experience with older students is that… they have… come to… realizations on their own. They’ve gone through their 20’s and they’ve kind of settled things out, and most of them recognize they have trade offs to do in life. Most of them, because they are older… want [to] be back in school. They’re here for a reason. They don’t like their jobs. They don’t want to be making minimum wage for the rest of their lives. They are far more committed. Their problems tend to be more of, “I can’t do it all.” (p. 83) Participants in Swain and Hammond’s (2011) study expressed similar notions and observed that nontraditional students committed to studies and contributed more to class activities than traditional students. The participants postulated that the older students were motivated to do their best because of the sacrifices they had made in deciding to attend college. These findings are consistent with a study of 300 randomly selected undergraduate students at a Midwestern university which found that nontraditional students selfreported slightly more overall motivation and significantly more intrinsic motivation than traditional students. Nontraditional students also tended to gain more satisfaction and increased interest in learning than their traditional peers (Bye, Pushkar, & Conway, 2007). These findings are 28 somewhat inconsistent with a study conducted by Justice and Dornan (2001), in which traditional and nontraditional students reported similar levels of motivation, study habits, selfefficacy, strategy use, and selfregulation, with older female students reporting the highest level of intrinsic motivation. Jameson and Fusco (2014) found that traditional and nontraditional students had similar levels of math selfefficacy in regard to functional math such as fractions and decimals, but not in regard to “areas of math that are perceived as more academic” (p. 313). Nontraditional students reported significantly lower levels of math selfefficacy in areas such as geometry and trigonometry, which may “stem from a lack experience with these tasks” (p. 313). Justice and Dornan (2001) noted no agerelated difference in the successful completion of the class. It is common for college students of all ages to consider dropping out of college, but the percentage of doubters and the reasons for doubting if they should continue their college career may vary between traditional and nontraditional students. A study of 172 psychology students enrolled in an English university revealed that slightly more than 43% of all participants doubted whether they should continue college enrollment (Xuereb, 2014). Whereas nearly 60% of traditional students reported doubting, only slightly more than 40% of nontraditional students doubted whether or not they should continue. Traditional students most commonly cited high academic workload and difficulties related to coursework as reasons for doubting continued enrollment in college. Nontraditional students, on the other hand, most commonly referred to outside responsibilities and personal or financial problems as primary reasons for doubting. Among all participants, “the most commonly cited reasons for continuing university studies was to achieve his or her end goal, closely followed by wanting to finish something he or she had started” (Xuebreb, 2014, p. 152). Traditional students, however, were more likely to report that 29 they decided to continue their college education because they wanted to finish what they started or that they had “experienced a positive change,” while nontraditional students were more likely to report that they continued due to support offered from university staff and support services (p. 152). Swain and Hammond (2011) found that nontraditional students may enroll or reenroll in college because they are more focused or more comfortable with themselves, or because they are in a better situation to attend college as an adult than they were or would have been as a traditionally aged college student. This supports Strage’s (2008) finding that older students and transfer students reported feeling more comfortable than traditional students with instructors, more confident in asking questions, and more likely to view instructors as a resource to help them learn. On the other hand, Justice and Dornan (2001) found that nontraditional students may also feel less confident than traditional students in using study skills effectively and in being able to succeed in college. HollisSawyer (2011) observed, however, that no relationship exists between older students’ perception of their ability and their actual performance. Academic Needs of Nontraditional Students Traditional and nontraditional students have different ideas about college courses and instructors. Strage (2008) studied 1,310 4year undergraduates and observed that older students (23 years or more) were tended to describe an ideal instructor as organized and flexible and the ideal course as organized, whereas younger students (1822) described an ideal instructor as funny and enthusiastic. For the traditional students, the ideal course was fun, easy, and active. Transfer students described the ideal course as being relevant to realworld and career interests. Older students tended to view college as a preparation for a career and valued coursework relevant to their career experience and aspirations (Compton et al., 2006; Strage, 2008). 30 Nontraditional students may study and learn differently than traditional students and may need assistance and guidance in developing effective study strategies (Justice & Dornan, 2001). Kenner and Weinerman (2011) charged instructors with helping adult students replace existing learning strategies with effective academic learning strategies, noting that adult students may resist abandoning learning strategies that have been effective in other areas of life. Kenner and Weinerman (2011) also indicated that older, goaloriented, students benefit from detailed syllabi and coursework that relates to other classes or to life outside of academia. Goddu (2012) recommended using situational or experiential learning, including roleplaying and problembased learning which allow adult students to use the new learning in practical ways. Instructorled lectures, still common in higher education, do not allow adult learners to integrate life experiences effectively into the lesson. According to Goddu (2012), all adult learning theories emphasize the importance of experience, and combining life experience with adult learning theory increases adult learning. Jesnek (2012) referred to a “digital divide” that exists between nontraditional students and college campuses. Nontraditional students are more likely than traditional students to lack the basic computer, word processing, and digital research skills that are expected in most college courses. Nontraditional students are also more likely to be unfamiliar with online portals, classroom management systems, and email, which are considered to be basic college skills. Learning these new skills is often very time consuming and may lead to increased anxiety and frustration for nontraditional students. Jesnek (2012) recommended the implementation of a noncredit essential computer skills course for students lacking the skills necessary for success in college. 31 Nontraditional Student Enrollment Nontraditional students are the fastest growing segment of the undergraduate student population, increasing from 30% of the total undergraduate population in 1996 to 50% in 2006, with 73% of all undergraduates possessing at least some characteristics of nontraditional students (CarneyCrompton & Tan, 2002; Newbold et al., 2010). Older students are significantly more likely than traditional students to be enrolled parttime as opposed to fulltime, which may be a reflection of older students’ increased work and family responsibilities (Calcagno et al., 2007b). In 2010, students 25 years of age and older comprised 64% of the parttime enrollment and 18% of the fulltime enrollment in U.S. 4year colleges and universities. In the same year, this group of students made up 52% of the parttime enrollment and 27% of the fulltime enrollment at U.S. 2year colleges (Chronicle of Higher Education, 2012). Factors contributing to a rise in nontraditional enrollment may include: (a) a weak economy, (b) global outsourcing, (c) aging Baby Boomers, (d) increasing technology, and (e) the need for new job skills (Jesnek, 2012). Horn, Cataldi, and Sikora (2005) noted that the longer students delayed college enrollment, the less likely they were to enroll fulltime or halftime, and the less likely they were to pursue a bachelor’s degree. Approximately 30% of students who delayed college entry by one year were pursuing a bachelor’s degree compared to 20% who delayed enrollment by 24 years, 10% who waited 59 years, and only 8% of those who delayed college enrollment by 10 years or more. Academic Success and Completion Rates for Nontraditional Students Newbold et al. (2010) found that nontraditional students maintained an average GPA of 3.5862 compared to an average GPA of 3.3772 for traditional students. This distribution represents a statistically significant difference on a 4.0 scale. In a small study of 63 female juniors and seniors, CarneyCrompton & Tan (2002) found that nontraditional female students 32 performed better academically than their traditional female peers, despite having increased family and work obligations and a limited support network. Nontraditional female students in CarneyCrompton and Tan’s (2002) study averaged 40.29 years, which may indicate that the older women had older children and a naturally increased selfefficacy due to their experience and maturity. Traditional students are more likely to be fulltime students and to graduate in less time than nontraditional students. Calcagno et al. (2007a) determined that traditional students were more likely to complete a community college degree or certificate in 17 trimesters than nontraditional students. Similarly, Newbold et al. (2010) found that 67.8% of nontraditional students take at least 5 years to complete a bachelor’s degree, compared to only 11.3% of traditional students. Pontes and Pontes (2012) identified dropout risk factors typically associated with nontraditional students including: independent student status, single parenting, having dependents, parttime enrollment, not being a high school graduate, fulltime employment, and delayed college enrollment. Over 70% of all U.S. undergraduates have one of these risk factors which classify them as being fairly nontraditional (Pontes & Pontes, 2012). After controlling for ability, determined primarily by placement test scores and enrollment patterns, Calcagno et al. (2007a) found that older students were more likely than their traditional counterparts to graduate from college. 33 Nontraditional students are significantly more likely than traditional students to experience an enrollment gap, meaning that they are enrolled in only part of an academic year (Pontes & Pontes, 2012). In 2008, 48.5% of all nontraditional students compared to only 15.8% of traditional students experienced a gap in enrollment during that academic year. Pontes and Pontes (2012) found that among nontraditional students, those who were enrolled parttime were more likely to experience an enrollment gap than those who were enrolled fulltime. In addition, nontraditional students who were financially independent were more likely to experience an enrollment gap than nontraditional students who were not financially independent. Pontes and Pontes (2012) noted an unexpected finding; however, that fulltime employment was not a significant risk factor for an enrollment gap among nontraditional students. Nontraditional students also tend to meet academic milestones, such as the accrual of a specified number of credit hours or completion of a specified percentage of the overall program, at a slower rate than traditional students (Calcagno et al., 2007b). Although reaching certain academic milestones increases the odds of degree completion for all students, Calcagno et al. found that nontraditional students were not impacted as much as their younger counterparts were by reaching or not reaching those milestones. For example, completing 20 nonremedial credits increased younger students’ likelihood of graduating by more than seven times. Older students who completed 20 nonremedial credits increased their chances of graduating by less than five times, however. Similarly, younger students who completed 50% of a program increased their odds of graduating by more than 15 times. Older students who completed 50% of the program, on the other hand, increased their chances of graduating by only 11%. In addition, older students were found to be less influenced by enrollment in developmental classes than were traditional age students. Calcagno et al. (2007b) maintained that nontraditional learners may benefit more 34 from flexible scheduling, varied course delivery formats, and childcare than from intense tutoring and advising that are often helpful to younger students. Texas Core Curriculum The Texas Core Curriculum is the general education requirement for Texas undergraduate students and provides the foundation for undergraduate degrees. The Texas Core Curriculum is determined by the THECB under the rules and guidelines of the Texas Education Code, determined by state legislation, and the Southern Association of Colleges and Schools Commissions on Colleges (SACSCOC), the regional accreditation body to which Texas is subject (THECB, 2011). Texas Education Code Section 61.821 defines the Core Curriculum as “the curriculum in arts, humanities, and sciences and political, social, and cultural history that undergraduate students of an institution of higher education are required to complete before receiving an academic undergraduate degree.” The Texas Core Curriculum accounts for one third of bachelor’s degree requirements , and once completed, is transferable as a unit to other Texas institutions (THECB, 2011). The SACSCOC requires a minimum of 15 semester credit hours (SCH) of Core Curriculum for an associate degree and at least 30 SCH for a baccalaureate degree, including at least one course from each of the following categories: humanities/fine arts, social/behavioral, and natural sciences/mathematics. The SACSCOC requires that these general education courses ensure a “breadth of knowledge” and do not “narrowly focus on those skills, techniques, and procedures specific to a particular occupation or profession” (SACSCOC, 2011, p. 19). The Texas Education Code 61.822, on the other hand, requires a minimum of 42 SCH of Core Curriculum for an undergraduate degree (Texas Education Code). Texas institutions must receive approval from the THECB to require a core curriculum in excess of 42 SCH (THECB, 2011). 35 The Education Advisory Committee (EAC), established in 2006, was charged with reviewing the Core Curriculum standards implemented in 1999. The EAC and the THECB determined that the Core Curriculum no longer served the needs of students and should therefore be revised to help ensure a smooth path to degree completion and preparation for 21st Century careers (THECB, 2011). The EAC also determined that the 1999 Core Curriculum was not sufficiently aligned with SACSCOC (2011) Core Requirement 2.7.3 which states that the Core Curriculum “…ensures breadth of knowledge…” and “…the courses do not narrowly focus on those skills, techniques, and procedures specific to a particular occupation or profession” (p. 19). One goal of the revised Core Curriculum, which was implemented in 2014, is to work within the framework required by SACSCOC and Texas statute and to move away from a set of isolated skills and toward a broader unit of interdisciplinary knowledge, skills, and competencies to include: (a) communication skills, (b) critical thinking skills, (c) empirical and quantitative skills, (d) teamwork, (e) social responsibility, and (f) personal responsibility (THECB, 2011). In the area of mathematics, which has a three SCH requirement, this revision meant that the previous objectives focusing primarily on quantitative literacy in realworld situations would be revised to include mandated objectives related to critical thinking, communication, and empirical and quantitative skills. Developmental Education History of Postsecondary Developmental Education Postsecondary developmental education in the United States began at Harvard College in 1636 as an effort to provide a literate pool of ministers to the colonies (Dotzler, 2003). During the early to mid1800s, private colleges, widely accessible to men who could bear the expense of higher education, employed tutors to support students who were underprepared for college, 36 primarily due to the period’s lack of available secondary schools. By 1889, developmental education was available at over 80% of postsecondary institutions (Dotzler, 2003). Cost of Developmental Education Developmental education cost the United States $1.3 billion during the 20042005 academic year and in excess of $2 billion per year by 2012 (Pretlow & Wathington, 2012). State expenditures for developmental programs have also increased over time. Developmental education accounted for $206 million of the 20062007 Texas biennium budget. Controlling for inflation, this represented a 5.5% increase over the $153.4 million spent on developmental education during the 19961997 biennium, when 2.25% of all Texas higher education funding was used for developmental programs (Pretlow & Wathington, 2012). Inconsistency among Developmental Education Programs Despite the cost to the American public, developmental math courses have become a barrier to degree completion, as a large proportion of students who enroll in the developmental mathematics sequence never complete it and therefore never earn a college credential (Bonham & Boylan, 2012). Some states, including Virginia, Texas, North Dakota, Louisiana, Colorado, and Alaska have created task forces to research the need, effectiveness, and objectives of developmental education and to develop an action plan or policy to address, correct, or improve these programs (Wilson, 2012). States such as Tennessee, North Dakota, New York, Missouri, Minnesota, Louisiana, Florida, and Colorado have adopted policies preventing 4year colleges and universities from offering developmental programs. In addition, three states, Nevada, South Carolina, and Nebraska, have eliminated state funding for developmental education at 4year colleges and universities (Wilson, 2012). At a time when budgetary constraints and state policies force 4year institutions to refer underprepared students to community colleges for their 37 developmental preparation, some 2year colleges no longer offer the lowest level developmental classes and have set limits on the amount of time students may take to complete the sequence (Pretlow & Wathington, 2012). There are no national standards for college readiness skills, but 35 states, including Texas, have policies to guide student placement in developmental courses (Wilson, 2012). Assessment instruments and score requirements vary and may not provide a true assessment of the student’s actual knowledge and skills (Bailey, 2009). Donovan and Wheland (2008) reported a high correlation between COMPASS I and ACT mathematics scores and success in intermediate algebra, but noted that although females may score lower on placement tests, they are significantly more likely than males to be successful in intermediate algebra. The Western Interstate Commission for Higher Education (Lane, Michelau, & Palmer, 2012) reported that the common practice of placing students in developmental courses based on one standardized test is a barrier to adult degree completion. Research indicates 4050% of these students could have successfully completed the entrylevel or “gateway” course without remediation. Assessment scores and the reliability of these scores in measuring student knowledge and skills may be influenced by a student’s failure to realize the importance of the placement test and by a lack of preparation and review for the test (Charles A. Dana Center et al., 2012). Bailey, Jeong, and Cho (2010) found that students originally directed to developmental courses, who chose instead to take entrylevel classes, had a slightly lower success rate than students not referred to developmental education, but a significantly higher success rate than students who did enroll in developmental courses, because only a small percentage of developmental education students ever enrolled in entrylevel classes. 38 Students who are successful in developmental mathematics may catch up with collegeready peers, but failing a developmental math course has been associated with significantly negative consequences (Fike & Fike, 2012). In a study of 3,476 firsttime college students, Fike and Fike found that students who passed developmental mathematics during their first semester had GPAs and retention rates similar to those of students who were academically prepared for college math when they started college. Students who needed developmental mathematics but did not enroll in it during their first semester had lower GPAs and lower retention rates than students who passed developmental mathematics their first semester, despite the fact that the group that delayed enrollment was better prepared than those who enrolled in the developmental course during their first semester. Students who failed developmental mathematics had lower overall GPAs than the other groups and were more than 80% less likely than their collegeready peers to return to college the following fall (Fike & Fike, 2012). Developmental Education Standards in Texas Although the use of college readiness assessments and results vary throughout the United States, the Texas Administrative Code (TAC) standardized the assessment and placement standards for all incoming students at Texas higher education institutions beginning with the 20132014 academic year (TAC). The TSI (Texas Success Initiative) Assessment is the only college readiness assessment approved by the THECB for use in Texas colleges and universities. With very specific and clearly defined exceptions, all incoming Texas college students are required to take the TSI Assessment. In addition, students are required to participate in a preassessment activity which includes information about the importance of the TSI test, examples of the test questions, an explanation of developmental education options, and information about resources available to help students succeed in college (TAC Title 19, Part 1, Ch. 4, Subch C, 39 Rule §4.55). Furthermore, all Texas higher education institutions are required to follow guidelines for referring students to developmental coursework or placing them in entrylevel classes. Texas higher education institutions are required to follow specific TSI passing standards which may not be raised or lowered. While TSI assessment results may not be used to deny student admission to an institution or program, the results are a required component of a holistic approach to course placement. The holistic approach also considers factors such as high school GPA, prior coursework, noncognitive factors such as motivation and selfefficacy, and familylife issues such as job responsibilities and childcare (TAC Title 19, Part 1, Ch. 4, Subch C, Rule §4.55). Texas institutions are required to provide an individualized academic plan to support students who do not meet the minimum TSI standards required to begin entrylevel coursework. The plan must include career advising, developmental education options, information about support services, a degree or program plan, regular contact with an advisor or other designee, registration information, and differentiated placement (TAC Title 19, Part 1, Ch. 4, Subch C, Rule §4.58). In addition, developmental coursework in Texas higher education institutions must be based on researchbased practices in assessment, differentiated instruction, and the integration of instructional technology. Developmental students in Texas also benefit from specialized support services, noncoursebased education interventions, and specially trained faculty (TAC Title 19, Part 1, Ch. 4, Subch C, Rule §4.62). Referral Rates and Correlations College students are referred to developmental courses in high, but varying, percentages. The Charles A. Dana Center et al. (2012) found that 50% of all U.S. undergraduate students and 70% of all U.S. community college students enroll in at least one developmental class. Parker 40 (2012) noted that 25% of students seeking a bachelor’s degree and 25% of students enrolled in a 4year college or university are placed into developmental coursework while 60% of students seeking an associate’s degree and 50% of students enrolled in a community college are placed into developmental classes. Pretlow and Wathington (2012) found that onethird of all firsttime college freshmen and up to 60% of all community college students require developmental education and that between 1996 and 2012, community colleges quadrupled the number of developmental classes offered in a distance education format. Bahr (2010) reported a high degree of correlation between mathematics and English deficiencies and remediation. Controlling for second language learners, 69% of students requiring no mathematics remediation also required no English remediation, whereas only 12% of students requiring the most intense mathematics remediation required no English remediation. The severities of the deficiencies were also found to be correlated. As severity in one subject increased, the likelihood of severity in the other subject also increased. Only 20% of students who began college deficient in mathematics and English, compared to 58% of students who began with no deficiencies, eventually reached entrylevel proficiency in both subjects (Bahr, 2010). A Barrier to Degree Completion The Charles A. Dana Center et al. (2012) suggested that developmental instruction serves to keep students out of entrylevel courses rather than increasing the chances of enrollment and success in courses such as college algebra. Evidence suggests that most developmental college courses do not include the teaching of paper writing skills or strategies designed to help students in areas such as test taking, note taking, and coping with the demands of work, family, school, and social expectations. In a study of 756 community college students, Wolfle (2012), found 41 that firstsemester students who enrolled in developmental mathematics were retained from first to second year at rates comparable to firstsemester students who enrolled in entrylevel mathematics. Over 72% of the developmental mathematics students in the study, however, never enrolled in an collegelevel mathematics course, which is consistent with research indicating that 87% of developmental mathematics students in Texas community colleges never complete entrylevel mathematics (Complete College America, 2013). According to the Charles A. Dana Center et al. (2012) college success is correlated to early enrollment in the student’s academic field. Developmental course sequences delay entry into these major area courses and increase the dropout risk. More than half of the students who enter concentration area classes during the first academic year either graduate from the community college or transfer to a 4year institution within five years. The 5year graduation or transfer rate drops to 20% if enrollment in major area classes is delayed until the third year of college enrollment (Charles A. Dana Center et al., 2012). Community college students who successfully complete the developmental sequence earn associate degrees or transfer to another institution at similar rates to students not requiring remediation, regardless of the number of developmental courses or subjects required (Bahr, 2010). Only 2533% of all developmental mathematics students ever complete the developmental mathematics sequence, however, and only 16% of students who begin three levels below college mathematics complete the developmental sequence within three years. Seventytwo to eighty percent of students requiring remediation never enroll in an entrylevel course (Bahr, 2008; Charles A. Dana Center et al., 2012; Templin, 2011; Wolfle, 2012). High attrition rates in developmental course sequences are linked to lower graduation rates. In a study of 85,894 students from 107 California community colleges, Bahr (2008) found 42 that 81.5% of students who enrolled in developmental mathematics did not earn an associate’s degree or transfer to another institution within eight years. This is consistent with the studies conducted by the Charles A. Dana Center et al. (2012) and Parker (2012) which indicated that approximately 75% of community college developmental education students fail to earn a degree or to transfer within eight years. Parker (2012) also found that only 32% of all students enrolled in developmental education earn a bachelor’s degree in six years as opposed to 58% of students who never enrolled in developmental classes. Developmental Mathematics and Age Developmental education enrollment is high among older students. Nearly half of all Texas college freshman ages 25 or older require at least one developmental class. Of these, only 13% of those enrolled in a community college, and 19% of those enrolled in a 4year college, go on to complete the associated entrylevel course (Complete College America, 2012). Older students are also significantly more likely than younger students to be placed in the lowest levels of developmental courses, especially in mathematics. This is of particular concern for nontraditional students as Le, Rogers, and Santos stated, “Students who hit a roadblock in the lowest levels of developmental mathematics are the most at risk for giving up on ever earning a postsecondary credential” (2011, p. 2). A study of 500 university students who failed to meet requirements to enroll in college algebra found that older students were significantly more likely than traditional students to be placed into the lowest level of developmental mathematics (Walker & Plata, 2000). An analysis of 35,073 students found that nontraditional students, students 25 years of age and older, scored an average of 87 points lower on mathematics placement exams but 29 points higher on verbal skills assessments than traditional students. Researchers noted that the difference in scores might 43 have been due to a combination of nontraditional students’ extended time away from formal mathematics instruction while still being required to use communication skills in the work place and social settings (Calcagno, et al., 2007a). Penny and White (1998) studied 1,475 developmental mathematics students from three universities and found that student age had a weak positive correlation with success in the highest levels of developmental mathematics, and Calcagno et al. (2007b) found that, while enrollment in developmental mathematics decreased the probability of college graduation for all students, older students seemed to be less negatively impacted than younger students. Other researchers have reported comparable success and persistence rates for traditional and nontraditional students who enroll in developmental mathematics courses (Little, 2002; Walker & Plata, 2000; Wolfle, 2012). Calcagno et al. (2007b) suggested that older students who are not seriously deficient in math or English may benefit from taking shorter refresher courses instead of fullsemester remedial courses prior to enrolling in collegelevel courses. Predicting Success Doyen (2012) found that for community college students who had completed intermediate algebra, the highest level of developmental mathematics, success in college algebra was highly correlated to the intermediate algebra assessment score and the intermediate algebra course grade. Doyen (2012) found that students who scored the highest on the intermediate algebra assessment and those who earned the highest grade in the intermediate algebra course were the most successful in college algebra. Although Doyen’s study included only 134 purposefully selected students who enrolled in a developmental mathematics course in the previous calendar year, the results are consistent with Penny and White’s (1998) conclusion that for developmental mathematics students, success in the highest level of developmental 44 mathematics is the strongest predictor of success in college algebra. Conversely, Doyen (2012) determined that enrollment in prealgebra, the second level of developmental mathematics, had a strong negative correlation with success in college algebra. Students who enrolled in prealgebra were less likely to be successful in college algebra than students who had been enrolled in intermediate algebra but not prealgebra. This finding is consistent with Donovan and Wheland’s (2008) finding that students who were placed directly into intermediate algebra were more successful in the course than students who previously enrolled in a lower level developmental mathematics class. Although this pattern may be an expected outcome, it is important to note that the objective of the lower level course is to prepare students for intermediate algebra. A study of 125 community college developmental mathematics students revealed a negative relationship between mathematics anxiety and achievement scores. Woodard (2004) found no significant variance in mathematics anxiety between traditional and nontraditional students but noted that achievement scores for both groups decreased as mathematics anxiety increased. The Charles A. Dana Center et al. (2012) noted that the shame and disappointment associated with repeating high school curriculum, often with high school instructional strategies, leads to higher rates of attrition among developmental students. Nontraditional students, however, are less affected by the negative impact of enrollment in developmental classes, especially developmental mathematics, than are traditional students (Calcagno et al. 2007b). Affective factors also influence the success of developmental mathematics students. Chadwick’s (2013) study determined that effective developmental mathematics instructors are aware that they are the most important variable in the learning environment. Content knowledge and the ability to teach were found to be of secondary importance to affective qualities such as 45 treating students with respect, developing positive relationships with students, providing an encouraging and nonjudgmental environment, reducing math anxiety and feelings of inadequacy, and being patient. In addition, the most successful developmental mathematics instructors were identified as those who maintained high standards, encouraged students to take responsibility for their learning, focused more on learning than on the students’ lack of knowledge, and were engaging. Developmental mathematics students were also found to be more successful when they were enrolled in smaller classes, were able to use a math lab, and had multiple learning opportunities such as a review of content, homework assignments, and varied assessments Chadwick, (2013). Redesigning Developmental Mathematics Programs “For many community college students, the traditional course delivery model— students attend a semesterlong lecture class several times per week—does not lead to success in developmental math” (Le, Rogers, & Santos, 2011, p. 3). As a result, colleges and universities are exploring alternate course delivery models, including accelerated classes, math labs, relating specific math skills to students’ intended majors, and offering technology enhanced instruction to support students and move them more quickly into creditbearing courses. Le, Rogers, and Santos argued that statewide initiatives would be necessary to establish, maintain, and reproduce successful developmental mathematics programs and recognized the THECB for providing funding and support to develop “innovative and effective developmental education programming” (p. 10). Research indicates that developmental programs are not an effective method of preparing students to be successful in entrylevel mathematics (Bailey, 2009). The Charles A. Dana Center et al. (2012) have developed a set of seven Core Principles to redesign and repurpose 46 developmental classes. These principles focus on acceleration over remediation and call for students to be placed in major courses early in their college career. The principles also call for multiple assessment measures before placing students in classes and requiring academic support classes as corequisites rather than prerequisites to college algebra. The Charles A. Dana Center et al. (2012) recommended either a onesemester corequisite class to support students through gateway classes such as entrylevel mathematics, or a oneyear plan specifically designed to support significantly underprepared students through entrylevel courses over the course of a full year. Research indicates that students who participate in the accelerated model are two to four times more likely to complete the entrylevel class than students who are placed one to two levels below college mathematics (Charles A. Dana Center et al., 2012; Complete College America, 2013). In a similar study, the National Center for Academic Transformation partnered with 38 community colleges to redesign developmental mathematics courses using technology and an acceleration model in which students participated in small course modules targeting their specific areas of weakness. This approach led to a 30% reduction in the cost of instruction and 31% increase in the student success rate (Templin, 2011). The Charles A. Dana Center et al. (2012) concur with the principle of individualized instruction, stating that developmental and support classes should be designed to meet the needs of students from particular majors, instead of attempting to prepare every student for college algebra. College Algebra Why College Algebra? Why is college algebra important? Hagerty, Smith, and Goodwin (2010) claimed that the processes and concepts learned in college algebra prepare students to be successful in subsequent 47 coursework outside the mathematics department. After extensive collaboration with representatives from “partner disciplines” including science, social sciences, and the arts, the Mathematics Association of America (MAA) found that representatives from the partner disciplines largely agreed that entrylevel college mathematics classes should be relevant, pleasant, and thoughtful experiences that develop students’ mathematical and logical reasoning skills and prepare them to become knowledgeable citizens and employees. Representatives from the partner disciplines also asserted that entrylevel college mathematics courses should provide a foundation for courses in other fields, develop student’s ability to communicate mathematical ideas, and should promote enrollment in additional mathematics courses (Ganter & Haver, 2011). In response to these findings, the MAA published college algebra guidelines designed to support the other disciplines. These guidelines include fundamental experience, course goals, competencies, and an emphasis on pedagogy (Ganter & Haver, 2011, pp. 4546). The MAA maintained that college algebra should provide students with fundamental experience that emphasizes algebraic reasoning and problem solving in the mathematics course, in other coursework, and in life outside of academia. The fundamental experience portion of the guidelines also indicated a need for students to address realworld problems through the creation and interpretation of mathematical models. In addition, the MAA recommended that students formulate, solve, and analyze problems using a variety of methods including mental strategies, pencil and paper, and technology (Ganter & Haver, 2011, p. 45). Although the MAA college algebra course goals included strengthening students’ algebraic and quantitative skills required in other disciplines, they also focused on the development of related skills. The MAA course goals called for a “meaningful and positive, intellectually engaging, mathematical experience” that allows students to collaborate, explore, 48 and communicate mathematical ideas (Ganter & Haver, 2011, p. 45). The MAA also called for the development of student confidence, the ability to use technology to solve problems, and the encouragement of students to take additional mathematics classes. The MAA’s college algebra competencies included problem solving in realworld situations. According to the guidelines, college algebra should emphasize the creation, interpretation, and revision of models to solve problems and students should develop personal problem solving strategies such as rereading a problem, sketching a diagram, identifying variables, and determining the plausibility of a solution. In addition, the MAA maintained that students should be expected to understand and use functions, rate of change, equations, and appropriate data collection to model and solve realworld problems (Ganter & Haver, 2011, p. 46). Finally, the MAA college algebra guidelines called for an emphasis on pedagogy and a variety of assessment tools and methods. Instructors were encouraged to create an environment “conducive to exploratory learning, risktaking, and perseverance,” to “encourage a conceptual understanding of mathematics,” to provide studentcentered learning opportunities, and to utilize technology such as calculators and spreadsheets. According to the guidelines, assessments should be designed to measure mastery of the course competencies including problem solving, mathematical arguments, and communicating mathematical ideas orally and in writing (Ganter & Haver, 2011, p. 46). The Argument against College Algebra for All College algebra is often a required element of general undergraduate education or core requirements, with up to 98% of students on some college campuses taking the class as a requirement rather than as an elective (Herriott & Dunbar, 2009). Introductory college 49 mathematics classes such as college algebra may serve as a roadblock to degree completion, especially for students who are uninterested in the material or who have mathematics related anxiety based on prior experience (Thiel et al., 2008). Although a vast majority of college students are required to take college algebra, nearly half of the 1,000,000 annual enrollees fail the course, and only 20% reenroll within the next 11 to 12 semesters (CortesSuarez & Sandifer, 2008; Gordon, 2008; Herriott & Dunbar, 2009; Thiel et al., 2008). A small study of two community colleges in Georgia revealed that college algebra and math modeling, the lowest creditbearing mathematics course at one of the institutions, had a higher rate of withdrawals and final grades of D and F than did freshman composition, American government, biology, and macroeconomics (Herriott & Dunbar, 2009). The rate of college enrollment has grown at approximately five times the rate of the U.S. population since the end of World War II (Gordon, 2008). Whereas college students were once the most academically and mathematically qualified students prepared for an algebraically intense calculus course, this is no longer the case. College algebra and precalculus classes were originally intended to prepare weaker students for calculus. Gordon (2008) found that although fewer than 15% of college algebra students intend to take calculus, the curriculum and focus of college algebra classes have remained largely unchanged over the past 50 years and do not sufficiently prepare students for the digital world. Herriott and Dunbar (2009) found that 31.9% of the nearly 1,500 college algebra students at a Midwestern state university went on to register for calculus for management and social science majors, and only 11.2% enrolled in Calculus I. Enrollment in Calculus II and III was even lower at 4.2% and 1.3% respectively. College algebra is the terminal mathematics class for a majority of students and may not adequately meet the needs of most college students (Gordon, 2008; Herriott & Dunbar 2009). 50 The Charles A. Dana Center et al. (2012) maintained that college algebra should not be a required course for students when other college mathematics classes would be more appropriate for a specific field of study. Gordon (2008) maintained that it is a disservice to most students to continue the practice of using lowerlevel general education mathematics courses such as college algebra to serve the needs of mathematics majors who comprise only a small percentage of the student body. High school students are taking more mathematics classes than before, but are referred to developmental education in increasing numbers (Gordon, 2008). High school teachers focus more on concepts and problem solving and incorporate more technology and calculator usage into their classes. A smooth transition to college mathematics has remained elusive, however, as placement tests and college coursework continue to focus on processes, formulas, and traditional mathematics (Gordon, 2008). In addition, although enrollment in college calculus has remained steady or declined slightly since the late 1990s, high school dual credit and AP calculus completions have increased at an average annual rate of 8% over the same period. Consequently, today’s most prepared students do not need firstyear college calculus. It is possible that college calculus will eventually become more of a developmental course than an entrylevel mathematics class (Gordon, 2008). College algebra is financially lucrative for colleges and universities. It is reportedly one of the least expensive and most frequently offered creditbearing mathematics classes, often taught by parttime faculty and teaching assistants. Gordon (2008) asserted, however, that mathematics departments exist to serve the needs of other departments by preparing students for classes in other disciplines. If college algebra and other mathematics classes do not meet the needs of these other departments, then the departments may cease to require these courses and 51 the mathematics department will be left with little more than developmental course offerings. Nontraditional Student Success in College Algebra HollisSawyer (2011) found that undergraduate students over the age of 40 reported higher levels of mathematics and testrelated anxiety and lower levels of confidence in their ability to be successful in mathematics. Believing that a negative stereotype exists about older students’ mathematics abilities may be a contributing factor to the reduced confidence levels, even when no significant difference exists in actual mathematics performance. Studies investigating a correlation between student age and success in college algebra have produced varying results, with success being defined as completing the course with a grade of A, B, or C. Wolfle (2012) found that students aged 23 and older were 1.36 times more likely to succeed in college algebra than their 1722 yearold classmates. Penny and White (1998) observed a weak positive correlation between student age and improved performance in college algebra but noted that most of the students were under 29 years, and that there was no evidence of improved performance for students who were significantly older than traditional age students. Doyen’s (2012) study of 134 community college students who had completed intermediate algebra in the previous calendar year found that 79% of enrolled students 25 and over completed college algebra successfully, compared to 66% of students ages 1822. The canonical structure coefficients, however, revealed a weak correlation between age and success in college algebra. Conversely, Calcagno et al. (2007b) found that older students, who had taken developmental mathematics courses enrolled in and passed college algebra at a lower rate than did traditional age students who had taken developmental mathematics courses. 52 Course Scheduling, Student Age, and Success in College Algebra Researchers have examined the correlations between course scheduling, student age, and success in college algebra. Gallo and Odu (2009) found that, regardless of age, students enrolled in classes that met two or three times per week were significantly more successful than students enrolled in classes that met only one time per week. Reyes (2010) examined the pass rates for students enrolled in 8week and 16week college algebra classes at a metropolitan community college in the United States. He found that 2330yearold students performed significantly better in the 16week course than in the 8week course. Course length was not a significant factor for 3140yearold students. Redesigning College Algebra The Western Interstate Commission for Higher Education (WICHE; Lane, Michelau, & Palmer, 2012) identified redesign of gateway classes, especially entrylevel mathematics, as a “promising practice” (p. 46) for reducing the barriers to adult degree completion. According to Gordon (2008), students need more exposure to and more practice with exponents and logarithms throughout their mathematics course rather than isolating them into only a chapter or a few sections; more practice with concepts and processes that carry over into other disciplines; more nonroutine, conceptual problems that have realworld applications, multiple perspectives, and multiple ways to solve the problem; realistic problems to solve rather than artificial problems that do not transfer to real situations; and an in depth conceptual understanding of algebraic reasoning and processes so that the skills will transfer to other disciplines and apply to the real situations. 53 Technology plays an important role in the course redesign for college mathematics courses. Butch and YuJu (2010) found that students who enrolled in classes using a computerized, masterybased, textbookcoordinated homework system performed better on exams than students enrolled in classes that used the traditional pencil and paper homework method. This concurs with previous findings by Hagerty and Smith (2005) who noted that students enrolled in evening classes, typically nontraditional students, did not show the same benefit from the computerized masterybased homework system and reported having less time than daytime students to log into a computer to complete the assignments. Instructors in Butch and YuJu’s (2010) study reported that the computerized homework helped the class move more smoothly, improved class discussions, reduced grading time, and allowed students to track their grades online. Although students in the computerized homework classes performed better on exams, the paper and pencil homework grades were a better predictor of exam grades, likely due to instant feedback and the allowance of multiple attempts to answer computerbased homework problems. Butch and YuJu, (2010) also noted a higher retention rate in the computerized homework classes. Eightysix percent of the students in the computerized homework classes finished the class, compared to 58% of the students in the pencil and paper classes. The University of MissouriSt. Louis also used technology to redesign college algebra to create a more active learning environment (Thiel et al., 2008). Lecture sections were reduced from three 50minute sessions per week to one 50minute session per week. The remaining class periods were replaced with time in the computer lab which allowed students to participate in active, handson, and collaborative learning. Software that complimented the textbook provided instructions, practice, tutorials, and guided solutions. Students were allowed to retry homework problems as many times as they desired, were rewarded with instant feedback and higher grades 54 when they answered problems correctly, but were held firmly accountable for deadlines. Weekly quizzes, unit tests, and a final exam were also completed in the lab. Instructors used class lecture time to introduce new or difficult concepts, guiding students through the course, and reviewing for upcoming tests. Students learned the mathematics by doing it rather than by listening to it. Student attitudes regarding mathematics improved and the pass rate increased from 55% to over 75% in three years. These results are consistent with the results of a similar study in which the mathematics faculty at a regional Midwestern university worked with faculty from the psychology department to redesign college algebra courses in a similar fashion (Hagerty et al., 2010). In addition to increasing the pass rate from 54% to 75% between 2002 and 2006, the university also noted a 0.5% increase in overall GPA, and a 300% increase in trigonometry enrollment. Although the efforts to redesign college algebra have been successful, they have not been free of challenges. Thiel et al. (2008) noted that barriers to course redesign included funding; instructor release time to design curriculum and test the program; and resistance to change. Online Classes Growth of Online Instruction Although the total enrollment in U.S. higher education dropped by 0.1% between the fall of 2010 and the fall of 2011, the percentage of college students enrolled in at least one online class actually increased by 9.3% during the same period (Allen & Seaman, 2013). In 2011, some 6.7 million postsecondary students, or 32% of all U.S. higher education students, were enrolled in at least one online class. This increase represents a compound annual growth rate of 17.3% over the 1.6 million U.S. college students enrolled in at least one online class in the fall of 2002 (Allen & Seaman, 2013). 55 In 2011, 91% of all U.S. 2 year colleges offered online classes (Parker, Lenhart, and Moore, 2011). By 2012, 62% of all U.S. postsecondary institutions, or 70% of all public and 48% of all private institutions, offered at least one completely online degree program and over 86% of all U.S. higher education institutions offered at least some online course options (Allen & Seaman, 2013). In addition, a 2011 report by Parker et al. indicated that 58% of colleges that offer online courses also offer at least one completely online degree program and 88% of residential colleges that offer online courses make those courses available to students who live on campus. Approximately 46% of U.S. students who graduated from college between 2001 and 2011 had taken at least one online course. Distance education, including enrollment in online courses, has also increased in Texas. In the fall of 2012, distance education accounted for 12.8% of the total Texas public higher education enrollment. This number represents a steady increase in fall to fall distance education enrollment percentages since 2002, when distance education comprised 2.45% of the total public postsecondary enrollment in Texas (THECB, 2013a). During the same period, online enrollment in Texas higher education courses has grown from representing 0.4% of the total enrollment in 2002, to accounting for 6.03% of the total enrollment in 2012 (THECB, 2013a). Perceptions of Online Instruction A survey of higher education leaders revealed a disconnect between their views and the opinions and practices of postsecondary institutions, presidents, faculty, and students (Allen & Seaman, 2013). The percentage of U.S. higher education leaders who viewed online instruction as a critical aspect of their institution’s longterm plan increased from less than 50% in 2002 to over 69% in 2012. However, only 60% of academic leaders from institutions offering entirely online programs and 30% of those from institutions offering online classes thought that their 56 institution’s strategic plan adequately reflected the importance of online instruction. While 77% of academic leaders viewed online instruction as equal to or better than live instruction, only 30% believed that faculty view online instruction as valuable and legitimate, and 57% remained neutral about faculty acceptance (Allen & Seaman, 2013). In addition, although 51% of university and college presidents believed that online courses are equal to or better than live courses, presidents of public institutions are more likely to believe this than presidents of private institutions, and only 29% of American adults agree (Parker et al., 2011). Whereas 39% of adults who have taken online classes described those classes as being of equal educational value to live courses, only 27% of adults who have not taken online classes subscribed to the same opinion (Parker et al., 2011). Advantages and Disadvantages of Online Instruction Students choose to enroll in online classes for a variety of reasons. Harris and Martin (2012) found that the most commonly reported reasons for taking online classes were related to time and location factors. Nearly twothirds of the online students included in Harris and Martin’s study indicated that the ability to complete assignments at a convenient time was a primary motivation for enrolling in an online class. Slightly over half of the online students in the study indicated that they enrolled in online classes because the commute to campus was too far or inconvenient. Fortyfive percent of the online students indicated that the ability to earn a degree and meet family obligations was a primary motivating factor for enrolling in online classes and an equal number cited the ability to take classes and meet employment requirements as an important factor. Other motivations for enrolling in online classes included course scheduling conflicts (27%), the ability to take summer classes while traveling (17%), and a preference for online learning (17%). These findings are consistent with Mahoney’s (2009) 57 conclusion that “Flexibility was the main reason participants enrolled in the online classes. The online classes allowed participants to have more control over their school and work schedules” (pp. 8182). While some participants in Mahoney’s study indicated that the flexibility of the online course increased the time they could work, others indicated that it allowed them to use their time more efficiently, which included allowing them to study at times that were quiet and they could work in solitude. Ghaffari (2011) identified several advantages to online classes from the student perspective. Primary among these was flexibility in both scheduling and location. Ghaffari maintained that online classes allow students to adjust their school schedule around life preferences and responsibilities, rather than requiring them to adjust their life to meet the demands of a specified class schedule. For some students, this may be related to the desire to avoid early morning classes. For others, including nontraditional students, online classes may be the only option that fits their already demanding schedule. Ghaffari noted that online courses allow students to take classes almost anywhere around the globe without requiring them to relocate or to commute to a specified location. Ghaffari also noted the additional advantages of increased access to class notes and lecture transcripts and the increased possibility of instructional technology and multimedia in online classes. Although administrators, faculty, and students cite advantages to online higher education opportunities, there are also disadvantages and barriers to online instruction. Student selfdiscipline is viewed as a key barrier to online classes. Ghaffari (2011) noted that online classes require students to have superior time management, selfregulation, and communication skills. In addition, 88% of academic leaders in 2012 indicated that online courses necessitate more student selfdiscipline than live classes (Allen & Seaman, 2013). Ghaffari (2011) and Harris and 58 Martin (2012) found that students in online classes may experience decreased communication with instructors and classmates, reduced access to tutoring services, and the inability to transfer online coursework into traditional degree programs. Participants in Mahoney’s (2009) study also reported feeling disappointed with the lack of technology, redundancy in assignment requirements, unclear assignment expectations, and limited access to the instructor. Institutional barriers to online instruction include: (a) higher attrition rates in online classes, (b) lack of employer acceptance of online programs, and (c) lack of faculty acceptance of online instruction. The Online Student Online students tend to be older than traditional live students and have typically earned more credit hours than students enrolled in the live versions of the same class (Wilson & Allen, 2011; Harris & Martin, 2012). A survey of online students indicated that they most frequently experienced written assignments, clear grading policies, multiple choice assessments, timely responses to emails and phone calls, and peer communication in online discussion boards (Harris & Martin, 2012). Infrequent experiences cited by online students included the availability of synchronous class discussions, video lectures, proctored tests, effective use of multimedia instructional tools, and interaction with instructors via the online message boards. Successful Versus Unsuccessful Online Students Wilson and Allen (2011) found cumulative GPA to be the best predictor of success for online and live students, but research suggests other factors may predict student success in online classes. Fetzner (2013) found that the most successful online students were at least 25 years of age, registered for classes at least 5 weeks prior to the start of the semester, and had previously earned a higher number of credit hours. Online students also identified the availability of technical support as important in successful completion of online courses (Beaghan, 2013). 59 A survey of 488 community college students who had previously been unsuccessful in at least one online class indicated that they did not know what to expect in an online course, how to get assistance in the class, or how much time and organization would be required to be successful (Fetzner, 2013). Nearly half of the participants revealed that they did not realize that they were required to begin the course on a specific date. The study also revealed that nearly 20% of the students surveyed attributed their failure to falling behind in class and not being able to complete all of the assignments. Approximately 28% indicated that personal problems, work, and family responsibilities were the primary reasons they were unsuccessful in the online course. Additionally, approximately 21% of the unsuccessful online students attributed their failure to an aversion to the online format, distaste for the instructional style, or “too many technical difficulties” (Fetzner, 2013, p. 15). Other participants indicated that that the primary reasons they were not successful in at least one online course were that the class required too much time (6.2%), a lack of personal motivation (5%), a heavy course load (4.3%), and course difficulty (3%). Fetzner (2013) supported a mandatory online orientation for firsttime online students to address issues such as (a) time management, (b) understanding course requirements, and (c) knowing how to find technical and academic support, which was identified by unsuccessful online students as important information to share with new online students. When asked if they would take another online class in the future, 31.3% of unsuccessful online students said there was no chance at all or that it was not likely. An additional 16.2% responded that it was possible, and 52.5% indicated that they were somewhat or very likely to take another online class (Feztner, 2013). 60 Online instructional strategies that support adult learning theory may contribute to the success of adult online students. Snyder (2009) recommended that online instructors employ several strategies to engage and retain adult students in online classes. First, it is important that instructors establish relationships with students and encourage them to connect with their fellow students. Then, it is important that instructors have effective practices for online instruction such as being consistent and predictable, facilitating communication and collaboration, and accommodating various learning styles. Snyder (2009) also recommended that online instructors encourage a shared responsibility for class leadership, provide accessible and relevant resources, acknowledge student contributions, utilize the internet for information and tools, and allow time for closure and reflection. In addition, Harris and Martin (2012) suggested that colleges and universities focus on faculty development and support in increasing both the amount and variety of instructional technology and multimedia tools used in online classes. A Comparison of Course Delivery Methods Ashby, Sadera, and McNary’s (2011) comparative study of three course delivery formats for intermediate algebra revealed patterns in student enrollment. The study included 167 community college students who selfselected enrollment into a completely live, a blended, or a completely online class. Thirtyfive percent of students enrolled in a live class, 28% enrolled in a blended class, and 38% enrolled in an online class. Students under 20 years of age showed a strong preference for live classes, students 2024 years of age were equally split between the three methods, and students 2549 years of age preferred the online option, comprising 70% of the total online enrollment. Ashby et al. (2011) also noted performance and success patterns across the three delivery methods. Students in the blended class fared the worst with the highest percentage of missing 61 grades, the lowest rate of completion, and a completer pass rate that was higher than the live course, but lower than the online class. Students in the live class had the lowest percentage of missing grades and the highest rate of completion, but also had the lowest completer pass rate of the three methods. The number of missing grades and the completion rates for the online class fell between that 
Date  2015 
Faculty Advisor  Scott, Joyce A 
Committee Members 
Travis, Jon Reid, Mark 
University Affiliation  Texas A&M UniversityCommerce 
Department  EdD Supervision, Curriculum, and InstructionHigher Education 
Degree Awarded  Ed.D. 
Pages  126 
Type  Text 
Format  
Language  eng 
Rights  All rights reserved. 



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