Exploring Factors Related to Completion of an Online Undergraduate-Level Introductory Statistics Course

Whitney Alicia Zimmerman, Glenn Johnson

Abstract


Data were collected from 353 online undergraduate introductory statistics students at the beginning of a semester using the Goals and Outcomes Associated with Learning Statistics (GOALS) instrument, an abbreviated form the Statistics Anxiety Rating Scale (STARS), a survey of expected grade and expected time commitment, and the first lesson quiz. At the end of the semester, whether or not each student successfully completed the course with a grade of D or higher was recorded. It was hypothesized that students who successfully completed the course would have had favorable ratings on each of these variables. While there were no significant differences between students who did and did not successfully complete the course in terms of anxiety, attitudes, or expected time commitment, students who completed the course had higher scores on the GOALS, higher expected grades, and higher scores on the first quiz of the semester. Stepwise logistic regression found that students’ attitudes towards statistics teachers and scores on the first quiz of the semester could be used to predict whether or not students would successfully complete the course. Based on these findings, suggestions for online instructors are given.

Keywords


Course completion; Attrition; Retention

Full Text:

PDF

References


Author. (2015).

Author. (Under review).

Aragon, S. R., & Johnson, E. S. (2008). Factors influencing completion and noncompletion of community college online courses. The American Journal of Distance Education, 22, 146-158.

Atchley, T. W., Wingenbach, G., & Akers, C. (2013). Comparison of course completion and student performance through online and traditional courses. International review of research in open and distance learning, 14(4), 104-116.

Azar, F. S., & Mahmoudi, L. (2014). Relationship between mathematics, self-efficacy, and students’ performance in statistics: The mediation role of attitude toward mathematics and mathematics anxiety. Journal of Educational Science & Psychology, IV(LXVI), 32-42.

Bälter, O., Cleaveland-Innes, M., Pettersson, K., Scheja, M., & Svedin, M. (2013). Student approaches to learning in relation to online course completion. Canadian Journal of Higher Education, 43(3), 1-18.

Bloemer, B. (2009). The UIS model for online success. Journal of Asynchronous Learning Networks, 13(3), 99-115.

Carr, S. (2000). As distance education comes of age, the challenge is keeping the students. The Chronicle of Higher Education, 46(23), A39-41.

Clark, M., Holstrom, L., & Millacci, A. M. (2009). University of Cincinnati: Case study of online student success. Journal of Asynchronous Learning Networks, 13(3), 99-115.

Cruise, R. H., Cash, R. W., & Bolton, D. L. (1985). Development and validation of an instrument to measure statistical anxiety. ASA Proceedings of the Statistical Education Section, American Statistical Association. Alexandria, VA. 92-97.

Fasse, R., Humbert, J., & Rappold, R. (2009). Rochester Institute of Technology: Analyzing student success. Journal of Asynchronous Learning Networks, 13(3), 99-115.

Hanna, D., Shevlin, M., & Dempster, M. (2008). The structure of the Statistics Anxiety Rating Scale: A confirmatory factor analysis using UK psychology students. Personality and Individual Differences, 45(1), 68-74.

Lock Morgan, K. (2015). Statistics Department 2015 Assessment. Unpublished internal report.

Meyer, K. A., Bruwelheide, J., & Poulin, R. (2009). Why they stayed: Near-perfect retention in an online certification program in library media. Journal of Asynchronous Learning Networks, 13(3), 99-115.

Sami, F. (2011). Course format effects on learning outcomes in an introductory statistics course. MathAMATYC Educator, 2(2), 48-51. Retrieved from www.amatyc.org/resource/resmgr/educator_feb_2011/sami-courseformat-feb11.pdf




DOI: http://dx.doi.org/10.24059/olj.v21i3.1017

Bookmark and Share