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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 Topic Teaching and Assessing with AI: Teaching Ideas, Research, and Reflections View all articles

Evaluating the Impact of Pattern Recognition on AI Skills Development in Universities

Provisionally accepted
Dinara Đšazimova Dinara Đšazimova 1Nurgul Serikbayeva Nurgul Serikbayeva 2*Gulfarida Samashova Gulfarida Samashova 1Anatoly Zatyneyko Anatoly Zatyneyko 1Botagoz Sarsenbayeva Botagoz Sarsenbayeva 3
  • 1 Buketov Karaganda State University, Karaganda, East Kazakhstan, Kazakhstan
  • 2 Semey State University, Semey, Kazakhstan
  • 3 Pavlodar Pedagogical University, Pavlodar, Kazakhstan

The final, formatted version of the article will be published soon.

    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

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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