CodeMentor-AI: AI-Powered Feedback Application for Programming in Open and Distance Learning

Authors

DOI:

https://doi.org/10.56059/jl4d.v13i1.1882

Keywords:

AI-generated feedback, Open and Distance Learning (ODL), self-managed learning

Abstract

This study examines CodeMentor-AI, an AI-powered tool that delivers immediate, adaptive and context-aware feedback on programming tasks. It supports iterative practice and self-managed learning to better prepare ODL learners for graded assessment. In a pilot focus group with eight ODL programming students, participants reported rapid assistance, clear understanding, practical gains, sustained engagement and motivation, and increased confidence to tackle the graded assessment and collectively strengthened self-managed learning.

Author Biography

Nantha Kumar Subramaniam, Open University Malaysia (OUM)

Nantha Kumar Subramaniam is a Professor at Open University Malaysia (OUM) with over 20 years of experience in computing, specialising in intelligent learning systems, natural language processing, and Computer Science Education. He previously served as Adviser for Technology-Enabled Learning at the Commonwealth of Learning (COL), Canada. Nantha has received numerous awards for his contributions to digital education, including the Best E-Learning Product at the International University Carnival on E-Learning (IUCEL) 2021 and multiple Gold Medals at Asian Association of Open Universities (AAOU) conferences for innovations in adaptive and intelligent learning systems. He is currently the Dean of the Faculty of Computing and Analytics at OUM, where he continues to lead initiatives in AI-driven learning, digital innovation, and open and distance education. Email: nanthakumar@oum.edu.my (https://orcid.org/0000-0002-5870-5949)

Published

2026-03-11

How to Cite

Subramaniam, N. K. (2026). CodeMentor-AI: AI-Powered Feedback Application for Programming in Open and Distance Learning. Journal of Learning for Development, 13(1), 198–204. https://doi.org/10.56059/jl4d.v13i1.1882

Issue

Section

Reports from the Field
Received 2025-01-27
Accepted 2026-01-09
Published 2026-03-11