Digital self-Efficacy as a foundation for a generative AI usage framework in faculty's professional practices

A new research paper, 'Digital self-efficacy as a foundation for a generative AI usage framework in faculty's professional practices,' provides a crucial roadmap for understanding AI adoption in academia. Led by researcher Fatiha Tali, the study surveyed 265 higher education faculty members to analyze their engagement with generative AI (GAI) tools like ChatGPT and Claude.

The core finding is the identification of three distinct user profiles based on survey data: 'Engaged' users who actively integrate AI, 'Reflective Reserved' users who are cautious and selective, and 'Critical Resisters' who largely avoid the technology. The research validated that these profiles are strongly associated with an individual's level of digital self-efficacy—a concept from Bandura's theory referring to one's belief in their ability to use digital tools effectively. This means an educator's confidence with technology is a key predictor of how they will use AI.

Contextually, this study moves beyond simply tracking AI tool usage. It applies sociotechnical theory to explain *why* adoption varies, framing GAI use as a process of 'appropriation' where users integrate technology into their existing professional practices. The practical implication is a proposed institutional support framework. Instead of one-size-fits-all training, the authors recommend differentiated strategies—such as tailored workshops, peer mentoring for 'Reflective' faculty, and clear ethical guidelines to address 'Critical' concerns—to help all educators, regardless of starting confidence, effectively leverage AI for teaching, research, and administration.