Artificial intelligence as a tool for analyzing and classifying programming problems in the educational process

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DOI:

https://doi.org/10.31865/2709-840082024316949

Abstract

The article considers the use of artificial intelligence as a tool for analyzing and classifying programming problems in the educational process. An approach to automating the problem classification process is proposed, which takes into account their complexity, subject matter, and type. Particular attention is paid to the advantages of using AI technologies to increase the efficiency of programming training, in particular, adapting problems to the level of students' knowledge. Practical results of implementing the problem classification system are presented, which demonstrate its high accuracy and prospects. The article also outlines the possibilities for further development of this area, such as the creation of adaptive platforms and recommender systems. The conclusions of the article emphasize the importance of integrating artificial intelligence into the modern educational process.

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References

Yao, Y., Duan, J., Xu, K., Cai, Y., Sun, Z., & Zhang, Y. (2024). A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly. High-Confidence Computing, Vol.4, Issue. 2, 100211. https://doi.org/10.1016/j.hcc.2024.100211

Murugesan, S. and Cherukuri, A.K. (2023). The Rise of Generative Artificial Intelligence and Its Impact on Education: The Promises and Perils. Computer, 56(5), pp.116–121. https://doi.org/10.1109/mc.2023.3253292

Величко В.Є., Ананьєв М.С., Іванюк С.В., Шеремет М.М. Електронне навчання у процесі вивчення програмування: Інформатика та методика її навчання. Збірник наукових праць фізико-математичного факультету ДДПУ, 2023, 13: 54-61. URL: https://doi.org/10.31865/2413-26672415-3079132023295330

Published

2024-12-05

How to Cite

Velychko, V., Ganiev, O., & Zhadan, S. (2024). Artificial intelligence as a tool for analyzing and classifying programming problems in the educational process. E-Learning TeXnology, 8, 66–73. https://doi.org/10.31865/2709-840082024316949

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