Analyzing of the Alignment between Course Learning Outcomes (CLOs) and Program Learning Outcomes (PLOs) Using Textual Similarity-Based Methods

Universities are the pinnacle of education in Indonesia to prepare the younger generation before entering the workforce. For example, in Indonesia, there is a government regulation (Permendikbudristek Number 53 of 2023) that concerning the Assurance of Higher Education Quality, each study program must define Program Learning Outcomes (PLOs) to achieve the university's objectives, which will then be translated into Course Learning Outcomes (CLOs) at the course level. Defining CLOs that align with specific PLOs is quite challenging. Therefore, in our study, we conducted an analysis of the alignment of PLOs and CLOs based on a text similarity approach. We modeled the PLOs and CLOs texts using TF-IDF and fastText representations, with cosine similarity as the similarity measurement. We evaluated the PLOs and CLOs from the computer science program at a university in Indonesia. The experimental results show that the fastText representation performs better in identifying the alignment between PLO and CLO, demonstrating its effectiveness in capturing semantic meaning beyond simple lexical similarities. This study highlights the importance of leveraging advanced text representation techniques to improve curriculum mapping and ensure a more structured and coherent learning outcome framework.