Needs Analysis for Developing Intelligent Digital Platform for Course Learning Outcome Assessment of Information Technology Program in Higher Education

This study aims to analyze the requirements for developing an intelligent digital platform for assessing Course Learning Outcomes (CLO) in undergraduate Information Technology programs within the framework of Outcome-Based Education (OBE). Traditional CLO assessment methods face several limitations, such as time-consuming manual evaluation and a lack of in-depth analysis for timely instructional improvement. This study explores expectations and key functions of the digital platform through surveys conducted among faculty members, students, and administrators. The findings indicate that students and faculty prioritize the need for an Artificial Intelligence Assessment System (AAS), while administrators emphasize the importance of a Reporting and Visualization System (RVS). These preferences align with expert evaluations, which identified the AAS as having the highest mean score (4.73), followed closely by the RVS (4.72). The overall mean score across all six components of the platform was 4.58, indicating a high level of importance. This research provides a foundational framework for developing an intelligent digital platform for CLO assessment in undergraduate Information Technology programs. Beyond facilitating learning outcome assessments, the platform has the potential to enhance the quality and efficiency of higher education teaching and learning in the future.