A formal model for assessing the learning outcomes of academic programs

Many academic programs face persistent challenges in evaluating learning outcomes with consistency, traceability, and alignment to curricular goals. This study introduces a formal model for the systematic assessment of learning outcomes across an academic program. The model is grounded in set theory and matrix algebra, integrates the SOLO taxonomy to classify levels of cognitive performance, and structures evaluation across three defined assessment moments: early, mid, and final stages of the academic trajectory.

The model was applied to a five-year teacher training program in Computer Science and validated through empirical data collection and statistical analysis. A paired t-test confirmed a significant decline in learning outcome performance between the initial and final stages of the program, while ANOVA results indicated consistent performance across courses at each stage. Based on these findings, the model also supports the generation of outcome-specific improvement plans, recalibrating performance expectations iteratively.

The proposed model contributes to outcome-based education by offering a replicable framework for aligning course-level evidence with program-level competencies. Its integration of structured assessment, cognitive benchmarking, and iterative feedback enables academic institutions to monitor student achievement longitudinally and support continuous curriculum improvement.