Artificial Intelligence Usage and Behavioral Academic Engagement Among Mathematics Undergraduates

<p>The rapid diffusion of artificial intelligence (AI) in higher education is transforming how students learn, interact, and engage with academic content. <em>Behavioral academic engagement</em> refers to students’ observable participation in academic activities, such as active involvement and completion of learning tasks, during mathematics learning with AI-related tools. This study examined the relationships among AI Technology Acceptance (AITA), Attitude Toward AI Use (ATTAIU), Behavioral Intention to Use AI (BIUAI), Actual Use of AI (AUAI), and Behavioral Academic Engagement (BAE) among mathematics undergraduates. Grounded in the Technology Acceptance Model (TAM), the study employed a quantitative, cross-sectional survey design involving 770 participants, drawn via purposive sampling from the mathematics education and mathematics science disciplines at four public universities in North-central Nigeria. Data was analyzed using SmartPLS 4.0 to test both measurement and structural models. The results revealed that AITA significantly and positively influenced ATTAIU (β = 0.774, <em>t</em> = 44.474, <em>p</em> < .001, <em>f</em><sup>2</sup> = 1.490) and BIUAI (β = 0.441, <em>t</em> = 21.966, <em>p</em> < .001, <em>f</em><sup>2</sup> = 0.269), while favorable attitudes toward AI predicted greater behavioral intention, actual use, and academic engagement. Actual use of AI strongly enhanced engagement (β = 0.553, <em>t</em> = 8.281, <em>p</em> < .001, <em>f</em><sup>2</sup> = 0.148), underscoring its vital role in transforming perception into action. Interestingly, behavioral intention alone negatively predicted engagement (β = −0.346, <em>t</em> = 4.715, <em>p</em> < .001, <em>f</em><sup>2</sup> = 0.042), suggesting that intention without meaningful application may hinder active learning. The findings extend TAM by demonstrating that acceptance and attitude predict BAE, providing theoretical and practical insights for integrating AI in mathematics education. The study concludes that cultivating acceptance, positive attitudes, and purposeful use of AI is key to advancing student engagement in the era of intelligent learning.</p>

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Publication Details

Journal
The International Journal of Learning in Higher Education
Published
2026-06-17
DOI
https://doi.org/10.18848/2327-7955/cgp/a349
Primary Topic
AI in Service Interactions
Type
article
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article

Artificial Intelligence Usage and Behavioral Academic Engagement Among Mathematics Undergraduates

Oluwanife Segun Falebita, Oluwayemisi Damilola Akomolafe, Olubunmi Kayode Ayanwoye, Lukman Shina Akinola
The International Journal of Learning in Higher Education
AI in Service Interactions
article

Artificial Intelligence Usage and Behavioral Academic Engagement Among Mathematics Undergraduates

Oluwanife Segun Falebita, Oluwayemisi Damilola Akomolafe, Olubunmi Kayode Ayanwoye, Lukman Shina Akinola
article en

Abstract

<p>The rapid diffusion of artificial intelligence (AI) in higher education is transforming how students learn, interact, and engage with academic content. <em>Behavioral academic engagement</em> refers to students’ observable participation in academic activities, such as active involvement and completion of learning tasks, during mathematics learning with AI-related tools. This study examined the relationships among AI Technology Acceptance (AITA), Attitude Toward AI Use (ATTAIU), Behavioral Intention to Use AI (BIUAI), Actual Use of AI (AUAI), and Behavioral Academic Engagement (BAE) among mathematics undergraduates. Grounded in the Technology Acceptance Model (TAM), the study employed a quantitative, cross-sectional survey design involving 770 participants, drawn via purposive sampling from the mathematics education and mathematics science disciplines at four public universities in North-central Nigeria. Data was analyzed using SmartPLS 4.0 to test both measurement and structural models. The results revealed that AITA significantly and positively influenced ATTAIU (β = 0.774, <em>t</em> = 44.474, <em>p</em> < .001, <em>f</em><sup>2</sup> = 1.490) and BIUAI (β = 0.441, <em>t</em> = 21.966, <em>p</em> < .001, <em>f</em><sup>2</sup> = 0.269), while favorable attitudes toward AI predicted greater behavioral intention, actual use, and academic engagement. Actual use of AI strongly enhanced engagement (β = 0.553, <em>t</em> = 8.281, <em>p</em> < .001, <em>f</em><sup>2</sup> = 0.148), underscoring its vital role in transforming perception into action. Interestingly, behavioral intention alone negatively predicted engagement (β = −0.346, <em>t</em> = 4.715, <em>p</em> < .001, <em>f</em><sup>2</sup> = 0.042), suggesting that intention without meaningful application may hinder active learning. The findings extend TAM by demonstrating that acceptance and attitude predict BAE, providing theoretical and practical insights for integrating AI in mathematics education. The study concludes that cultivating acceptance, positive attitudes, and purposeful use of AI is key to advancing student engagement in the era of intelligent learning.</p>

The International Journal of Learning in Higher Education
University of Zululand (ZA), Federal University Oye Ekiti (NG)
Quality Education
Openalex Percentile: Top 5%
AI in Service Interactions
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