Research by Scott Burrus

by Peggy Anthony published Sep 12, 2018 03:10 PM, last modified Oct 09, 2018 03:22 PM

Using Learning Analytics to Determine Predictors of Successful Completion for Online Students

Authors: Meena C. Clowes, Melanie E. Shaw, and Scott W. M. Burrus

Abstract: In this study, the researchers sought to determine predictors of (a) student success in learning tasks and (b) efficiency in student task attempts necessary to achieve success for at-risk students in an online learning environment. The study was informed by archival (de-identified) data gathered in the United Kingdom from students in an online education setting, which bears many similarities to American online higher education: namely, non-traditional student demographics, open enrollment, and a completely online education structure. A series of logistic regressions yielded two findings. First, the only statistically significant predictor of student success is the number of course attempts. Therefore, since number of attempts is a more statistically significant predictor of student completion than student demographics, understanding what influences how many course attempts students need in order to be successful can be more useful for targeted educational policy-making. Second, for those who only required one attempt to be successful, the number of previously studied credits was the only significant predictor. For those who required more than one course attempt, age was also a significant predictor. Thus, the number of credits students had prior to taking an online course is a useful predictor of whether a student is successful the first time they attempt an online learning module. For those who seem to need numerous attempts before being successful, age seems to be more of a statistically significant predictor than any other demographic factor.

Citation: Clowes, M. C., Shaw, M., & Burrus, S. (2017).  Using learning analytics to determine predictors of successful completion for online students.  The International Journal of Adult, Community and Professional Learning, 24 (2), 15-21.

A Comparative Typology of Student and Institutional Expectations of Online Faculty

Authors: Melanie E. Shaw, Meena C. Clowes, and Scott W. M. Burrus

Abstract: Online faculty must uphold institutional expectations for their performance. Typically, online institutions have specific guidelines for faculty-to-student interactions; yet, student expectations of faculty may not necessarily align with institutional requirements. This study included a typological analysis of institutional requirements for online faculty in terms of student engagement. Then, student comments regarding faculty performance expectations were compared. Based on the findings, there are substantive differences which should be considered by institutions to ensure online student satisfaction with faculty is maximized. Recommendations for further study include replicating this with a purposeful sample of online students and doing a quantitative study of the relationship between faculty outcomes after implementing student performance expectations.

Citation: Shaw, M, Clowes, M.C., & Burrus, S.W.M. (2017). A comparative typology of student and institutional expectations of online faculty. Online Journal of Distance Learning Administration, 20(2).