An Adaptive Learning Support System based on Ontology of Multiple Programming Languages

Nongkhai, Lalita N A; Wang, Jingyun; Mendori, Takahiko

Abstract

This research proposes to develop an adaptive ontology-based learning support system for computer programming learning. Firstly, the system adopts a previously developed ontology called CONTINUOUS, which represents programming concepts and their relation in a graph and makes use of its content to serve as hints within programming questions. Secondly, we design an adaptive strategy for recommending suitable exercises to learners, which uses CONTINUOUS as metadata of exercises and the Elo rating system to estimate learners' skills. This work aims to design a system to provide personalized exercise path for the learner and evaluate its effectiveness.

Citation

Nongkhai, L. N. A., Wang, J., & Mendori, T. (2023, December). An Adaptive Learning Support System based on Ontology of Multiple Programming Languages. Poster presented at ICCE 2023: The 31st International Conference on Computers in Education, Matsue, Shimane, Japan

• Presentation Conference Type: Poster
• Conference Name: ICCE 2023: The 31st International Conference on Computers in Education
• Start Date: Dec 4, 2023
• End Date: Dec 8, 2023
• Acceptance Date: Sep 1, 2023
• Publication Date: 2023
• Deposit Date: Oct 11, 2024
• Publicly Available Date: Oct 24, 2024
• Peer Reviewed: Peer Reviewed
• Volume: 1
• Pages: 141-143
• Book Title: ICCE Main Conference Proceedings - V1
• Keywords: Adaptive Learning Support; Ontology; Recommendation System; personalized learning; programming learning
• Public URL: https://durham-repository.worktribe.com/output/2954200
• Publisher URL: https://www.apsce.net/events/icce-2023