JCERJournal of Contemporary Educational Research2208-84662208-8474Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jcer.v10i7.15752ArticleAI-Supported Project-Based Learning Reform for the Data Structures Course under the “Less Teaching, More Learning” Philosophyhttps://artdesignp.com/journal/JCER/10/7/10.26689/jcer.v10i7.15752PuXiaoxia,ZhangJunli20261072026-08-06This study proposes an AI-supported project-based learning (PBL) framework for the Data Structures course under the Less Teaching, More Learning philosophy. The traditional chapter-based curriculum was reconstructed into eight authentic Python projects supported by the learning activity management system and a large language model-based AI teaching assistant. A controlled teaching experiment involving two undergraduate classes was conducted to evaluate the effectiveness of the proposed approach. The results indicate that the AI-supported PBL model significantly improved students’ academic performance, programming competence, and self-directed learning compared with conventional instruction. The proposed framework provides a practical and transferable paradigm for AI-enabled curriculum reform in computer science education.

Guo P, Saab N, Post LS, et al., 2020, A Review of Project-Based Learning in Higher Education: Student Outcomes and Measures. International Journal of Educational Research, 102: 101586.

Dalziel J, 2003, Implementing Learning Design: The Learning Activity Management System (LAMS). In: Proceedings of the 20th ASCILITE Conference, Adelaide, Australia, 593–596.

Brown TB, Mann B, Ryder N, et al., 2020, Language Models are Few-Shot Learners. Advances in Neural Information Processing Systems (NeurIPS), 33: 1877–1901.

Crompton H, Burke D, 2023, Artificial Intelligence in Higher Education: The State of the Field. International Journal of Educational Technology in Higher Education, 20(1): 22.

Li Z, Wang Z, Wang W, et al., 2025, Retrieval-Augmented Generation for Educational Application: A Systematic Survey. Computers & Education: Artificial Intelligence, 8: 100417.

Mullins EA, Portillo A, Ruiz-Rohena K, et al., 2024, Enhancing Classroom Teaching with LLMs and Retrieval-Augmented Generation. In: Proceedings of the ACM SIGITE Conference 2024, 237–243.

Zawacki-Richter O, Marín VI, Bond M, et al., 2019, Systematic Review of Research on Artificial Intelligence Applications in Higher Education: Where Are the Educators? International Journal of Educational Technology in Higher Education, 16: 39.

Cotton DRE, Cotton PA, Shipway JR, 2023, Chatting and Cheating: Ensuring Academic Integrity in the Era of ChatGPT. Innovations in Education and Teaching International, 61(2): 228–239.