A Procedural Learning and Institutional Analytics Framework

Data analyses provide the means for monitoring the quality of academic processes and the means for assessing the fiscal and operational health of an organization. Data-driven decision making can help to empower academic leaders, faculty, and staff with quantitative insights that guide strategies pertaining to enrollment and retention, student support and quality assurance, communication, bullying intervention, academic progress, and academic integrity. However, the integration of analytics into the institutional context is not a trivial process. Much of the analytics approaches discussed in the literature take a theoretical stance outlining main considerations but lacking the pragmatic edge. Our aim in this chapter is to assist academic leaders in undertaking analytics design and implementation. To this end, we synthesize the existing research and propose a procedural framework for integrating data analysis techniques and methods into a process that facilitates data-driven decision making by aligning institutional needs with actionable strategies.