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

被引:0
|
作者
Manly, Catherine A. [1 ]
机构
[1] Fairleigh Dickinson Univ, Peter Sammartino Sch Educ, Teaneck, NJ 07666 USA
来源
EDUCATION SCIENCES | 2024年 / 14卷 / 04期
关键词
student success; prescriptive analytics; action research; online education; LEARNING ANALYTICS;
D O I
10.3390/educsci14040413
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
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.
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页数:13
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