Evaluating the impact of pattern recognition on AI skills development in universities

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.

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Publication Details

Journal
Frontiers in Education
Published
2025-05-07
DOI
https://doi.org/10.3389/feduc.2025.1592209
Citations
3
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
6.85
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article

Evaluating the impact of pattern recognition on AI skills development in universities

Anatoly Zatyneyko, Dinara Кazimova, Nurgul Serikbayeva, Gulfarida SAMASHOVA et al.
3 citations
Frontiers in Education
Big Data and Business Intelligence
6.85
article

Evaluating the impact of pattern recognition on AI skills development in universities

Anatoly Zatyneyko, Dinara Кazimova, Nurgul Serikbayeva, Gulfarida SAMASHOVA, Botagoz Sarsenbayeva
article en
3 citations

Abstract

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.

Frontiers in EducationVol. 10
Karaganda Buketov University (KZ), Pavlodar State Pedagogical University (KZ), Semey Medical University (KZ)
Openalex Percentile: Top 4%
Big Data and Business Intelligence
6.85
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Evaluating the impact of pattern recognition on AI skills development in universities — Anatoly Zatyneyko, Dinara Кazimova, et al. · Frontiers in Education (2025) | TGRS Research Map | TGRS