Technology acceptance barriers to learning analytics adoption

Implications for inclusive education

Abstract

Learning analytics (LA) systems has potential to create inclusive educational environments supporting diverse learners in higher education. However, successful implementation depends on user acceptance by academic staff and administrators. This study examines factors influencing LA adoption in Australian universities through the Technology Acceptance Model (TAM). Using qualitative case study methodology, interviews were conducted with twenty-three participants across five demographically diverse Australian universities. Template analysis examined data according to TAM's core constructs: perceived usefulness, perceived ease of use, attitude towards use, behavioural intention, and actual system usage. Findings reveal that while participants recognised LA's potential for evidence-based decision making and personalised learning support, adoption was hindered by system complexity, data quality issues, and inadequate training. Power users demonstrated LA's capacity to enhance inclusive teaching through tailored interventions for at-risk students. Institutional barriers including fragmented systems, access restrictions, and policy constraints limited widespread adoption. Results suggest successful LA implementation requires user-centred design, comprehensive training, and institutional support structures. These findings thus provide practical insights for universities seeking to leverage learning analytics as inclusive technology promoting equitable educational outcomes.