Opportunities and Challenges of AI to Support Student Assessment in Computing Education: A Systematic Literature Review

Simone Santos, Gilberto S. Junior

2024

Abstract

This study investigates how Artificial Intelligence (AI) can support student assessment in computing education through a systematic literature review of twenty studies from the past decade. AI’s evolution has significantly impacted various fields, including education, offering advanced capabilities for personalized teaching, continuous evaluation, and performance prediction. Analysing these studies, evidence showed a focus on undergraduate students and the employment primarily face-to-face teaching methods, with engineering education and serious games being more cited contexts. These studies also reveal AI’s potential to create personalized learning experiences using techniques like fuzzy logic, KNN algorithms, and predictive models to analyse student interactions and performance, particularly in educational games and online courses. The positive findings demonstrate AI’s effectiveness in classifying students’ learning profiles, predicting employability, providing real-time assessments, facilitating targeted interventions, and improving learning outcomes through personalization. Automated assessments via AI have been shown to reduce teachers’ workload by offering accurate, real-time feedback. However, the studies also highlighted challenges concerning student engagement, teacher material quality, model generalization, and technical obstacles such as natural language processing, algorithm stability, and data cleaning. These data-driven factors emphasize the necessity for further advancements in AI to enhance continuous and effective student assessment as part of the personalized learning process.

Paper Citation

in Harvard Style

Santos S. and S. Junior G. (2024). Opportunities and Challenges of AI to Support Student Assessment in Computing Education: A Systematic Literature Review. In Proceedings of the 16th International Conference on Computer Supported Education - Volume 2: CSEDU; ISBN 978-989-758-697-2, SciTePress, pages 15-26. DOI: 10.5220/0012552500003693

in Bibtex Style

@conference{csedu24,
author={Simone Santos and Gilberto S. Junior},
title={Opportunities and Challenges of AI to Support Student Assessment in Computing Education: A Systematic Literature Review},
booktitle={Proceedings of the 16th International Conference on Computer Supported Education - Volume 2: CSEDU},
year={2024},
pages={15-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012552500003693},
isbn={978-989-758-697-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Conference on Computer Supported Education - Volume 2: CSEDU
TI - Opportunities and Challenges of AI to Support Student Assessment in Computing Education: A Systematic Literature Review
SN - 978-989-758-697-2
AU - Santos S.
AU - S. Junior G.
PY - 2024
SP - 15
EP - 26
DO - 10.5220/0012552500003693
PB - SciTePress