Towards a strengthened learning analytics and explainable artificial intelligence framework: An initial SWOT analysis

Abstract

The increasing use of learning analytics (LA) and artificial intelligence (AI) in education technology can benefit learning, resource allocation, and decision-making. However, issues remain in supporting the adoption of such systems and mitigating the multifaceted ethical, credibility, and interpretability challenges they pose. Developing a strengthened trustworthy LA and explainable AI (XAI) framework is crucial for the future of technology-rich education. This paper presents an initial SWOT analysis to systematically assess existing trustable LA and XAI frameworks in education. This analysis potentially empowers stakeholders to make more informed decisions about the choice of frameworks for evaluating the adoption and development of such systems. Moreover, insights from the analysis will provide a basis for creating a new framework for addressing and strengthening the gaps in existing frameworks.