2025 ASEE Annual Conference & Exposition

(Empirical Research Paper and Work In Progress) Artificial Intelligence (AI) is revolutionizing the educational landscape, offering innovative tools and opportunities for unique learning experiences. This shift has made it imperative to study its impact and methods of effective implementation across diverse educational fields. This study delves into how educators perceive and integrate AI into the TPACK framework to enhance education through technological knowledge (TK), pedagogical knowledge (PK), and content knowledge (CK). The research questions are: 1) How do faculty members conceptualize AI literacy in the TPACK framework? 2) How do faculty members' AI literacy levels influence their teaching approaches and strategies? 3) What challenges and opportunities do faculty members face in integrating AI into their teaching practices using the TPACK framework? Faculty members across various academic disciplines were interviewed. A sample size of 32 participants were interviewed; sixteen were from STEM, and sixteen were from non-STEM. This provides a broad horizon that permits data saturation and prevents confounding variables from the interviews.

Purposive sampling was used to select participants who were currently integrating or experimenting with the use of AI tools within their teaching practices. Selection focuses on those who are engaged with AI in educational practices and are willing to share their experiences. The goal is to gather detailed insights from these individuals to provide a robust outlook on AI integration. Additionally, this cross-sectional study aims to highlight the current methods and practices of AI integration into curricula. AI adoption is a relatively fresh concept. Different educators will have varied methods to incorporate AI into their teaching, especially across the different disciplines, regardless of AI’s evolution. Thus, with a focus on current methods, this qualitative study aims to highlight these applications across such fields. This potentially serves as a baseline for future studies that may be longitudinal in nature.

A semi-structured interview framework was used for the data collection. This would focus on the domains of TK, PK, and CK for an in-depth analysis, and allows faculty members to share their personal experiences and perceptions regarding AI literacy. These interviews lasted approximately 40 minutes and were guided by questions structured around the TPACK framework. The data was thematically analyzed. The data was coded to draw out recurring themes and patterns, analyzed various faculty’s AI literacy, and their influence on each TPACK component. The outcomes from this study were obtained via a deeper insight into how faculty members understand and integrate AI technologies into their teaching practices, using the TPACK framework. Additionally, it identifies the main challenges that faculty members face, and the support required to enhance their AI literacy, which can create professional development initiatives. Lastly, this study shows how AI literacy impacts pedagogical approaches and content delivery, increasing the literature on AI’s role in higher education.