Abstract
This participatory action research aims to demonstrate how information systems scholars, practitioners, and administrators of higher education collaborate to develop, implement, and evaluate effective predictive models and in turn create and adopt policies and procedures that improve student academic success and retention in a business college. This research takes a novel perspective by focusing on predicting student success and retention, informed by activity theory as the fundamental theoretical framework to understand the interactions among various stakeholders in the communities.
Recommended Citation
Schiller, Shu, "Predicting and Improving Academic Success and Student Retention: An Action Research" (2016). Proceedings of the 2016 Pre-ICIS SIGDSA/IFIP WG8.3 Symposium: Innovations in Data Analytics. 15.
https://aisel.aisnet.org/sigdsa2016/15