How Effective are AI Tools for Diverse Learners? A Case Study on Python and Data Science Education

Authors

DOI:

https://doi.org/10.21015/vtcs.v13i1.2075

Keywords:

AI tools; user experience; learning methodologies; educational technologies; interactive tasks.

Abstract

Artificial Intelligence (AI) based tools (such as ChatGPT) has revolutionized the learning methodologies for complex subjects by introducing the innovative methods in education. This study focuses on how AI tools can be helpful for the undergraduate students at Shah Abdul Latif University in learning the Python programming and Data science concepts. The study was conducted on beginners and intermediate groups of students through an organized survey by comparing their experiences gained through interactive tasks. The survey results reflect that intermediate users get more benefits from AI tools due to their familiarity with the technologies, whereas beginners face challenges in comprehension and ease of use. The study concludes recommending some practical suggestions to enable AI tools more effective, comprehensive and user-friendly.

References

Kim J, Lee H, Cho YH. Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education. Educ Inf Technol. 2022;27(5). doi:10.1007/s10639-021-10831-6.

Mittal U, Sai S, Chamola V, Devika. A comprehensive review on generative AI for education. IEEE Access. 2024. doi:10.1109/ACCESS.2024.3468368.

Cardona MA, Rodríguez RJ, Ishmael K. Artificial Intelligence and the Future of Teaching and Learning. Miguel A. Cardona Roberto J. Rodríguez Kristina Ishmael. 2023;(1):1–71. doi:10.13140/RG.2.2.28132.76160.

Bozkurt A, et al. Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape. Asian J Distance Educ. 2023;18(1):53. doi:10.5281/zenodo.7636568.

Popenici SAD, Kerr S. Exploring the impact of artificial intelligence on teaching and learning in higher education. Res Pract Technol Enhanc Learn. 2017;12(1). doi:10.1186/s41039-017-0062-8.

Fischer G, Lundin J, Ola J, Lindberg J. Rethinking and reinventing learning, education, and collaboration in the digital age—from creating technologies to transforming cultures. [Internet]. Available from: https://graderesearch.umu.se/forskarskolan-grade/conference2019/

Sari HE, Tumanggor B, Efron D. Improving educational outcomes through adaptive learning systems using AI. Int Trans Artif Intell. 2024;3(1):21–31. doi:10.33050/italic.v3i1.647.

Sayma SR. Creating effective multimedia learning material with AI for K12 learning & meaningful learning. 2024;233–44.

Hakimi M, Shahidzay AK. Transforming education with artificial intelligence: potential and obstacles in developing countries. Preprints. 2024 Jul 31. doi:10.20944/preprints202407.2542.v1.

Jian MJK O. Personalized learning through AI. Adv Eng Innov. 2023;5(1):16–9. doi:10.54254/2977-3903/5/2023039.

Holmes W, Bialik M, Fadel C. Artificial Intelligence in Education: Promise and implications for teaching and learning. 2019 [Internet]. Available from: https://www.researchgate.net/publication/332180327

Kordon AK. Data science based on artificial intelligence. In: Applying Data Science. Springer International Publishing; 2020. p. 3–37. doi:10.1007/978-3-030-36375-8_1.

Zhuang T, Lin Z. The why, what, and how of AI-based coding in scientific research. [Internet]. Available from: https://www.nature.com/articles/s41551-024-01185-8

Molina OE, Fuentes-Cancell DR, García-Hernández A. Evaluating usability in educational technology: A systematic review from the teaching of mathematics. LUMAT. 2022. University of Helsinki. doi:10.31129/LUMAT.10.1.1686.

Saqr RR, Al-Somali SA, Sarhan MY. Exploring the acceptance and user satisfaction of AI-driven e-learning platforms (Blackboard, Moodle, Edmodo, Coursera and edX): An integrated technology model. Sustainability. 2024;16(1). doi:10.3390/su16010204.

da Silva CAG, Ramos FN, de Moraes RV, dos Santos EL. ChatGPT: Challenges and benefits in software programming for higher education. Sustainability. 2024;16(3). doi:10.3390/su16031245.

Park Y, Doo MY. Role of AI in blended learning: A systematic literature review. 2024.

Almufarreh A. Determinants of students’ satisfaction with AI tools in education: A PLS-SEM-ANN approach. Sustainability. 2024;16(13). doi:10.3390/su16135354.

Chu HC, Hwang GH, Tu YF, Yang KH. Roles and research trends of artificial intelligence in higher education: A systematic review of the top 50 most-cited articles. 2024.

Zheng D. The criteria of Chinese regulatory framework on artificial intelligence: Reflections based on cost-benefit analysis. Preprints. 2023. doi:10.20944/preprints202312.2082.v1.

Downloads

Published

2025-05-06

How to Cite

Kehar, A., Abro, A., & Fatima, S. (2025). How Effective are AI Tools for Diverse Learners? A Case Study on Python and Data Science Education. VAWKUM Transactions on Computer Sciences, 13(1), 95–105. https://doi.org/10.21015/vtcs.v13i1.2075