Using Data Mining to Explore Why Community College Transfer Students Earn Bachelor's Degrees with Excess Credits. CCRC Working Paper No. 100

Autor/inn/en	Fink, John; Jenkins, Davis; Kopko, Elizabeth; Ran, Florence Xiaotao
Institution	Columbia University, Community College Research Center
Titel	Using Data Mining to Explore Why Community College Transfer Students Earn Bachelor's Degrees with Excess Credits. CCRC Working Paper No. 100
Quelle	(2018), (50 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Monographie
Schlagwörter	Community Colleges; College Transfer Students; College Credits; Bachelors Degrees; Data Analysis; Course Selection (Students); Comparative Analysis; Academic Records; Introductory Courses; Advanced Courses + Suchen Sie Ihr Suchwort? Community college; Community College; Hochschulwechsel; Schulwechsel; Studienortwechsel; College; Colleges; Achievement; Performance; Anrechnung; Hochschule; Fachhochschule; Leistung; 'Bachelor''s degrees'; Bachelor-Studiengang; Auswertung; Course selection; Student; Students; Kurswahl; University; Universities; Publication; Universität; Akademieschrift; Publikation; Einführungskurs; Fortgeschrittenenunterricht
Abstract	Community college transfer students encounter challenges progressing toward a bachelor's degree, leading to widespread transfer credit loss. This in turn may lower students' chances of credential completion and increase the time and costs for students, their families, and taxpayers. In this study we review three definitions of credit transfer inefficiency--"credit transferability," "credit applicability," and "excess credits among completers"--focusing on the last to examine why students who start at a community college and transfer to a four-year institution so often end up with excess credits that do not count toward a bachelor's degree. To shed light on credit transfer inefficiency, we examine the course-taking behaviors of community college transfer students who earn bachelor's degrees with numerous excess credits compared with transfer students who earn bachelor's degrees with few excess credits. We employ data-mining techniques to analyze student transcripts from two state systems, enabling us to examine a large number of variables that could explain the variation in students' excess credits at graduation. These variables include not only student demographics but also the types and timing of courses taken. Overall, we find more excess credits associated with several factors, including taking larger proportions of 100- and 200-level courses and smaller proportions of 300-level courses throughout students' progression toward completion, and taking 100-level courses in any subject--and specifically 100-level math courses--immediately after transferring to a four-year institution. Findings suggest that institutions could help students reduce credit transfer inefficiency by encouraging them to explore and choose a bachelor's degree major early on so they can take the required lower division (100- and 200-level) courses at the community college, thereby enabling them to take mostly upper division 300- and 400-level courses in their desired major field once they transfer to a four-year institution. (As Provided).
Anmerkungen	Community College Research Center. Available from: CCRC Publications. Teachers College, Columbia University, 525 West 120th Street Box 174, New York, NY 10027. Tel: 212-678-3091; Fax: 212-678-3699; e-mail: ccrc@columbia.edu; Web site: http://ccrc.tc.columbia.edu/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01