Digital self-Efficacy as a foundation for a generative AI usage framework in faculty's professional practices
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arXiv
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911458596487168 |
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| author | Tali, Fatiha |
| author_facet | Tali, Fatiha |
| contents | This research explores the role of digital self-efficacy in the appropriation of generative artificial intelligence (GAI) by higher education faculty. Drawing on Bandura's sociocognitive theory and Flichy's concept of usage framework, our study examines the relationships between levels of digital self-efficacy and GAI usage profiles. A survey of 265 faculty members identified three user profiles (Engaged, Reflective Reserved, Critical Resisters) and validated a three-dimensional digital self-efficacy scale. Results reveal a significant association between self-efficacy profiles and GAI appropriation patterns. Based on these findings, we propose a differentiated usage framework integrating four sociotechnical configurations, appropriation trajectories adapted to self-efficacy profiles, and personalized institutional support mechanisms. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2602_17673 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Digital self-Efficacy as a foundation for a generative AI usage framework in faculty's professional practices Tali, Fatiha Human-Computer Interaction Computers and Society This research explores the role of digital self-efficacy in the appropriation of generative artificial intelligence (GAI) by higher education faculty. Drawing on Bandura's sociocognitive theory and Flichy's concept of usage framework, our study examines the relationships between levels of digital self-efficacy and GAI usage profiles. A survey of 265 faculty members identified three user profiles (Engaged, Reflective Reserved, Critical Resisters) and validated a three-dimensional digital self-efficacy scale. Results reveal a significant association between self-efficacy profiles and GAI appropriation patterns. Based on these findings, we propose a differentiated usage framework integrating four sociotechnical configurations, appropriation trajectories adapted to self-efficacy profiles, and personalized institutional support mechanisms. |
| title | Digital self-Efficacy as a foundation for a generative AI usage framework in faculty's professional practices |
| topic | Human-Computer Interaction Computers and Society |
| url | https://arxiv.org/abs/2602.17673 |