BRIEF RESEARCH REPORT article
Front. Educ.
Sec. Digital Education
Volume 10 - 2025 | doi: 10.3389/feduc.2025.1592209
This article is part of the Research TopicTeaching and Assessing with AI: Teaching Ideas, Research, and ReflectionsView all 4 articles
Evaluating the Impact of Pattern Recognition on AI Skills Development in Universities
Provisionally accepted
- 1Buketov Karaganda State University, Karaganda, East Kazakhstan, Kazakhstan
- 2Semey State University, Semey, Kazakhstan
- 3Pavlodar Pedagogical University, Pavlodar, Kazakhstan
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Pattern recognition is a cornerstone of Artificial Intelligence (AI), shaping critical applications such as image analysis, speech processing, and automated decision-making. This study examines the impact of university curricula on developing AI competencies through dedicated pattern recognition training. A mixed-methods approach was employed to assess student comprehension, curriculum effectiveness, and challenges in mastering advanced concepts. The analysis reveals that structured coursework significantly enhances practical AI skills; therefore, recommendations include integrating more hands-on experiences and continuously updating course content. Such refinements promise to better prepare students for real-world challenges and industry demands. In conclusion, evolving instructional practices are essential for robust AI expertise.
Keywords: pattern recognition, Artificial intelligence education, AI Skills Development, machine learning, neural networks
Received: 19 Mar 2025; Accepted: 07 Apr 2025.
Copyright: © 2025 Кazimova, Serikbayeva, Samashova, Zatyneyko and Sarsenbayeva. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Nurgul Serikbayeva, Semey State University, Semey, Kazakhstan
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