Sustainable Education and Digital Transformation
Gendered paths of AI anxiety: Exploring self-competence and efficacy in college students
John Mark R. Asio 1 *
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1 Gordon College, Philippines
* Corresponding Author
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Sustainable Education and Digital Transformation, Online First, Article No: e44318
https://doi.org/10.33902/SEDT.202644318

Article Type: Research Article

Published Online: 13 Apr 2026

Views: 111 | Downloads: 35

ABSTRACT
In a world where artificial intelligence (AI) is slowly integrating itself into students’ lives, one thing is certain: it is inevitable. College students are adamant and still uncertain of AI’s potential. Hence, this study explores the complex relationships among AI anxiety, AI self-efficacy, and AI self-competency among college students. The study used a descriptive correlational research design employing a moderated mediation analysis with 1,006 convenience-sampled college students from a higher education institution in the Philippines. The study was also conducted during the 2nd semester of the 2024-2025 academic year. A standardized instrument was also used to determine AI anxiety, AI self-efficacy, and AI self-competence. Both descriptive statistics (means and standard deviations) and inferential statistics (Pearson’s r and multiple linear regression) were calculated using statistical software. Findings indicate average levels across the three constructs, with significant positive correlations observed between AI anxiety, AI self-efficacy, and AI self-competency. Gender, on the other hand, emerged as a moderating factor, influencing the relationships between AI self-efficacy and self-competency. Mediation analysis further demonstrated that AI self-efficacy significantly mediates the relationship between AI anxiety and AI self-competency. These results offer important insights into how cognitive and emotional factors interact in AI-related learning, contributing to a more nuanced understanding of students’ preparedness and adaptability in environments increasingly shaped by AI. The findings have implications for educational strategies that support students in technology-rich academic settings.
KEYWORDS
AI anxiety AI self-competence AI-self-efficacy gender moderation and mediation analysis Process Macro
In-text citation: (Asio, 2026)
Reference: Asio, J. M. R. (2026). Gendered paths of AI anxiety: Exploring self-competence and efficacy in college students. Sustainable Education and Digital Transformation. https://doi.org/10.33902/SEDT.202644318
In-text citation: (1), (2), (3), etc.
Reference: Asio JMR. Gendered paths of AI anxiety: Exploring self-competence and efficacy in college students. Sustainable Education and Digital Transformation. 2026. https://doi.org/10.33902/SEDT.202644318
In-text citation: (1), (2), (3), etc.
Reference: Asio JMR. Gendered paths of AI anxiety: Exploring self-competence and efficacy in college students. Sustainable Education and Digital Transformation. 2026. https://doi.org/10.33902/SEDT.202644318
In-text citation: (Asio, 2026)
Reference: Asio, John Mark R.. "Gendered paths of AI anxiety: Exploring self-competence and efficacy in college students". Sustainable Education and Digital Transformation (2026). https://doi.org/10.33902/SEDT.202644318
In-text citation: (Asio, 2026)
Reference: Asio, J. M. R. (2026). Gendered paths of AI anxiety: Exploring self-competence and efficacy in college students. Sustainable Education and Digital Transformation. https://doi.org/10.33902/SEDT.202644318
In-text citation: (Asio, 2026)
Reference: Asio, John Mark R. "Gendered paths of AI anxiety: Exploring self-competence and efficacy in college students". Sustainable Education and Digital Transformation, 2026. https://doi.org/10.33902/SEDT.202644318
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