Enhancing Novice Programming Education With an AI-Augmented Learning Tool

• In Event: Virtual Poster Session
  In Virtual iPresentation Only: Division C - Section 1e: Engineering and Computer Science Virtual Poster Session

Abstract

This study explores the development and implementation of an AI-augmented coding assistance tool designed for novice programmers. The tool’s impact on learning, problem-solving, and motivation in introductory programming courses was investigated using a mixed-methods approach. The study, grounded in Vygotsky's Zone of Proximal Development theory, cognitive load theory, and self-efficacy theory, was piloted with post-secondary and tertiary students from diverse educational contexts. Findings indicate that the AI tool effectively addressed common programming challenges, reduced cognitive load, and enhanced students' self-efficacy. The tool showed potential for promoting equity in computer science education. This research contributes to understanding how AI can enhance computer science education, particularly for beginners, and has implications for educational practice and policy.

Authors

• Kenneth Y.T. Lim, National Institute of Education - Nanyang Technological University

• Jing Qiang Toh, Nanyang Technological University

• Ahmed Hazyl Hilmy, National Institute of Education - Nanyang Technological University