A Personalized Method for Computing Course and Program Learning Outcome Attainment in Higher Education

Abstract

This study proposed a personalized outcome evaluation method for Outcome Based Education that traced assessment evidence from course components to Course Learning Outcomes and aggregated them into Program Learning Outcomes to support accreditation oriented quality assurance such as ABET and AUN-QA. A binary linkage matrix identified assessment components contributing evidence to each Course Learning Outcome, ensuring alignment with constructive alignment principles and Bloom’s taxonomy. Course Learning Outcome scores were calculated on a normalized scale from zero to one hundred using course grading weights and outcome specific evidence weights, and attainment was determined using a pre-defined threshold. Program Learning Outcome scores were obtained through weighted aggregation of related Course Learning Outcome scores, and results were reported using the Percentage of Program Learning Outcome Completion indicator for clear interpretation. A pilot implementation in one master’s program using data from five courses demonstrated high outcome attainment and identified weaker areas, thus providing auditable evidence and practical support for continuous program improvement.