Impact of Training on Faculty Perception of AI Knowledge: A Quantitative Perspective

Abstract

To effectively integrate AI into education, university instructors need to have AI-specific technological, pedagogical, and content knowledge (TPACK). Research indicates that university instructors often feel unprepared with these competencies; thus, they lack the knowledge to effectively integrate AI tools into their teaching practices. While substantial literature exists on AI in education, there remains a significant gap in faculty-centered research, particularly regarding instructor knowledge, comfort, and ethical understanding of AI implementation in higher educational contexts. This study examined faculty perceptions regarding their AI-TPACK knowledge, ethics-based AI knowledge, and then assessed whether those perceptions were influenced by training in AI tools. Using a quantitative descriptive cross-sectional research design that is based on Celik’s TPACK framework, this empirical research examined faculty members’ self-perceived competencies in each area. The study found that AI-focused professional development significantly enhanced faculty knowledge and comfort with AI integration among the 100 faculty members who participated in the study. Also, the findings revealed a critical gap in ethical AI knowledge, underscoring the urgent need for ethics-specific training to build faculty confidence in classroom implementation. Universities should leverage these findings to offer targeted professional development initiatives that close identified gaps and improve instructional effectiveness and faculty digital literacy skills.