Connecting Prescriptive Analytics with Student Success: Evaluating Institutional Promise and Planning

Author:

Manly Catherine A.1ORCID

Affiliation:

1. Peter Sammartino School of Education, Fairleigh Dickinson University, Teaneck, NJ 07666, USA

Abstract

Data-driven educational decisions enabled by online technologies hold promise for improving student performance across the full range of student dis/ability, even when efforts to design for student learning requirements (such as through Universal Design for Learning) fall short and undergraduates struggle to learn course material. In this action research study, 37 institutional stakeholders evaluated the potential of prescriptive analytics to project student outcomes in different simulated worlds, comparing hypothetical future learning scenarios. The goal of these prescriptions would be to make recommendations to students about tutoring and to faculty about beneficial course redesign points. The study’s analysis focused on the alignment of resources, processes, and values for feasible institutionalization of such analytics, highlighting institutional core values. In the postpandemic mix of online and on-campus learning under increasingly constrained resources, educational leaders should explore the potential competitive advantage of leveraging data from online technologies for greater student success.

Funder

Society for Learning Analytics Research

Publisher

MDPI AG

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