Regression analysis of self-regulatory concepts to predict community college math achievement and persistence
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Gramlich, Stephen Peter.
Regression analysis of self-regulatory concepts to predict community college math achievement and persistence. Retrieved from
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TitleRegression analysis of self-regulatory concepts to predict community college math achievement and persistence
Date Created2010
Other Date2010-05 (degree)
Extentix, 116 p. : ill.
DescriptionOpen door admissions at community colleges bring returning adults, first timers, low achievers, disabled persons, and immigrants. Passing and retention rates for remedial and non-developmental math courses can be comparatively inadequate (LAVC, 2005; CCPRDC, 2000; SBCC, 2004; Seybert & Soltz, 1992; Waycaster, 2002). Mathematics achievement historically has been a subject of concern with community colleges, universities, and primary schools (Davis, 1994; MEC, 1997; NCTM, 1989, 2000; Wang-Iverson, 1998). An important statistic of community colleges is that more than 83% of students work full or part-time (NEDRC, 2000; Phillippe & Patton, 2000). Conventional homework time estimates can range from 1-3 hours of homework for every hour of in-class instruction. Self-regulatory learning has been proposed to improve opportunity for math achievement (Bembenutty, 2005; Ironsmith et al., 2003; Jones & Byrnes, 2006; Pajares & Graham, 1999; Schunk, 1990). Seventeen research questions were made to explore the relative influences of goal setting, time planning, and time usage on mathematics achievement and persistence. Math students from 8 classes at a large, northeastern community college were administered 3 surveys asking self-regulatory questions.Results were found from descriptive statistics, frequency distributions, correlation matrices, t-tests, multiple regressions, and logistic regressions. Goal setting and time management were significant contributors in the model for predicting non-remedial students' final average. With respect to remedial students' final average, goal setting was related but all of the time planning and usage variables were not. Non-remedial students may have been more realistic about their course goals. However, non-remedial students were overly optimistic about allocating their time. No practical information regarding math student persistence beyond the first exam was found. Notable statistics from this study included: students spent about 5 to 6 hours per week on their math homework and over 80% worked at least 15 hours per week. Students worked more job hours on average than on all class homework. A possible recommendation to improve achievement is an extra class time for doing homework. Another implication is math educators, first-year workshops, and textbooks could teach the skills necessary for students to create suitable time management schedules and strategies that support students' course goals.
NoteEd.D.
NoteIncludes abstract
NoteVita
NoteIncludes bibliographical references
Noteby Stephen Peter Gramlich
Genretheses, ETD doctoral
LanguageEnglish
CollectionGraduate School of Education Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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