SUPPORTING ACCOUNTABILITY IN OUTCOME-BASED EDUCATION THROUGH AI-DRIVEN LEARNING ANALYTICS: A CASE STUDY AT THANG LONG UNIVERSITY

Abstract

Outcome-Based Education (OBE) positions accountability at the center of higher education by requiring institutions to demonstrate alignment between intended learning outcomes and verified student achievement. However, in practice, accountability mechanisms often remain procedural and fragmented, limiting their capacity to inform continuous improvement. Recent advances in artificial intelligence (AI) and learning analytics offer new possibilities for transforming accountability into a more systematic, data-driven process. This study examines how AI-assisted learning data analysis can strengthen accountability within an OBE-oriented program through a qualitative-dominant case study at Thang Long University, Vietnam. Drawing on institutional documents and aggregated assessment data, the analysis explores how AI-supported aggregation and outcome-level reporting enhance evidence-based decision-making. Findings indicate that AI-enabled analytics consolidate fragmented assessment data, identify outcome-level performance gaps, and support structured feedback loops linking evidence to curricular refinement. Rather than replacing academic judgment, AI functions as an infrastructural mechanism that strengthens the evidentiary foundations of accountability in OBE implementation.