Work

Intelligent Feedback for Individualized Introductory Programming Exercises

Year: 2025

Type: article

Abstract: ABSTRACT This paper proposes a method to improve programming instruction in an interdisciplinary Bachelor of Science and Technology program by integrating Artificial Intelligence (AI) into the code assessment process. Programming skills are a fundamental part of Engineering and Computer Science degrees. Using the Virtual Programming Lab plugin for Moodle, students complete parameterized exercises that generate unique problem instances and test cases for each individual. An embedded AI system, powered by a selection of seven widely used Large Language Models, analyzes students' code and provides automated feedback upon each correction request. This AI‐based approach promotes scalable assessment while supporting student autonomy. Preliminary results indicate significantly positive student perceptions across key pedagogical dimensions, including idea generation, clarity of explanations, learning autonomy, and feedback timeliness.

Source: Computer Applications in Engineering Education

DOI: 10.1002/cae.70132

Authors: Francisco de Assis Zampirolli, Fernando Teubl, Paulo Henrique Pisani, Thiago Alexandre Paiares e Silva

Institution: Universidade Federal do ABC

Language: English

Topic: Teaching and Learning Programming

Subfield: Computer Science Applications

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $4,150