A needs analysis for institutional analytics

Abstract

Institutional analytics (IA) can provide insights to support strategic planning in higher education. Despite its potential to reduce dropout rates, improve student performance, and support resource allocation, among other benefits, its adoption is mostly limited to small-scale implementations and isolated at the instructor level. To increase adoption, it is crucial to implement IA solutions that align with the needs of the different institutional stakeholders. This study explores institutional stakeholders' decisions that can be supported by IA, with the potential to inform strategies that could facilitate broader IA adoption across institutions. To do that, we conducted semi-structured interviews with 10 institutional stakeholders (covering, the head of studies, heads of academic directions, program administrators, and study counselors) to gain deep insights into their IA needs. We analyzed the data using Latent Dirichlet Allocation and thematic analysis. The results highlight that institutional stakeholders are interested in using evidence to inform decisions related to four areas: staff, students, general management and administration, and curriculum. Also, the results indicate that institutional stakeholders place greater emphasis on student-related decisions (such as identifying dropouts) and curriculum-related decisions (e.g. how to promote personalized learning, competency development, and student satisfaction). Additionally, this paper maps existing IA solutions to these needs and discusses theoretical and practical implications for institutions and researchers to promote IA adoption.