AI-Driven Learning Analytics for Outcome-Based Education in Higher Education Institutions

Abstract

With the recent emphasis on Outcome-Based Education (OBE), it has become even more essential that colleges and universities have excellent data-driven systems that are able to not only compile, evaluate and interpret learning evidence into measurable outcomes, but essentially do it accurately and comprehensively as well. The traditional way of implementing OBE tends to rely on imperfect assessment data, looking backward in time and lacking depth, which further handicaps it from being useful in executing continual enhancements and making rapid academic decisions as well. To address such a difficulty, there comes across a framework within this chapter that proposes needing data-driven systems that incorporate artificial intelligence (AI) into learning analytics as part of OBE systems as well. This chapter illustrates how AI is beneficial in increasing accuracy, monitoring, prediction and intelligent interventions regarding various types of institutional settings and is based on actual data and proves that primary data at an institutional level can be employed to reveal students’ actual engagement, their performance on tests and their success rates in accomplishing their goals within various programmes and academic cycles as well. To ensure that AI is used responsibly in the best interest of the institution and its stakeholders, the paper also addresses issues related to ethics, issues related to data governance challenges and readiness of the institution. This chapter offers a very useful and viable strategy for universities that are on a path of successful implementation of Outcome Based Education using AI learning analytics.