Motivated Strategies for Learning Questionnaire (MSLQ)
Category: Pathways to and Through Postsecondary
As predictive analytics become increasingly embedded in higher education, commercial vendors offering these tools play a growing role in shaping institutional decision making, particularly through identifying students deemed “at risk.” In this qualitative study, we analyzed 132 publicly available materials from 15 vendors to examine these companies’ marketing of predictive analytics. Drawing on Snow and Benford’s (1988) framing theory, we investigated how they construct the problem of student success and how they portray students in these constructions. Findings from our thematic analysis are: (1) the primary problem vendors purport to address is the lack of data insights to support student success, including due to data silos, capacity constraints, and the exclusion of student behavioral and engagement data; (2) vendors largely frame the problem their products address as one of institutional finances; and (3) vendors acknowledge structural barriers but rarely recognize students’ strengths. Although vendors frequently invoke equity-oriented language to position their tools as student-centered, our analysis reveals an emphasis on financial value for institutions and a limited engagement with students’ assets, ultimately narrowing pathways for supporting students’ success.
Keywords
Predictive Analytics, Community Cultural Wealth, Student Success, Student Success Outcomes
Education level
Document Object Identifier (DOI)
10.26300/dxjw-ps14
