Structuring Topics of Philippine Universities' Introductory Programming Courses Using Semi-Supervised Pairwise-Constrained Clustering to Synthesize Alternative Course Topic Outlines
Date of Award
5-1-2023
Document Type
Thesis
Degree Name
Master of Science in Computer Science
First Advisor
Jenilyn A. Casano, PhD
Abstract
In course design, topic outline organization encompasses the structuring and sequencing of topics to be delivered in a learning environment. Recent studies in topic outline optimization revolve around massive open online courses (MOOCs) due to their abundance but not much has been studied on the traditional courses. This study explores the organization of topic outlines in traditional introductory programming courses across Philippine higher education institutions (HEIs). By analyzing 16 course syllabi, A topic precedence graph (TPG) was created via a semi-supervised pairwise constrained k-means (PCK-Means) clustering to structure the topics which produced 20 topic clusters with strong topic cohesion within the clusters. The TPG showed that HEIs generally start the outline similarly, followed by core programming topics with varied sequences, and divergent ways of ending the outline. Two anomaly clusters were identified as having topic titles grouped that do not seem to have a unifying topic. This can be attributed to the limitations of the clustering algorithm where it cannot identify semantic meaning between words which may affect its applicability in situations where topic titles are named inconsistently. From the TPG, alternative optimal and comprehensive topic outlines were synthesized via greedy and DFS graph traversal algorithms. However, these alternative outlines performed very poorly when compared with the evaluators’ (n=19) arrangement of topic outlines due to some prerequisite topics being discussed in the latter part already. Overall, this study introduces a method to incorporate computer science technologies in aiding educators in topic outline design but more research is needed before it can be implemented in a real classroom setting.
Recommended Citation
Bayaras, Kleb Dale G., (2023). Structuring Topics of Philippine Universities' Introductory Programming Courses Using Semi-Supervised Pairwise-Constrained Clustering to Synthesize Alternative Course Topic Outlines. Archīum.ATENEO.
https://archium.ateneo.edu/theses-dissertations/969
