How are faculty and college students embracing AI? — A multi-informant mixed method study

This multi-informant mixed-methods study uses a concurrent parallel sampling approach to investigate undergraduate students' and faculty's perceptions of utilizing AI in teaching and learning at U.S. universities. A survey developed based on the Technology Acceptance Model, Social Influence Theory, and existing literature was implemented to collect undergraduate students' data regarding students' perceived AI learning environment, perceived others' attitudes toward AI, and personal attitudes toward AI. Faculty's opinions were collected through semi-structured interviews in accordance with the survey variables. Quantitative findings indicated that the effect of the AI learning environment on students' personal attitudes toward AI was fully mediated by their perceptions of others' attitudes. This finding highlights the critical role of perceived others' attitudes towards AI since students tend to adapt to the AI learning environment by mirroring the attitudes they perceive from others. The qualitative findings explored faculty's use of AI tools, their attitudes toward AI and students' usage, the challenges they experienced, and the need for clear guidance and support to facilitate better incorporation of AI into their professional practices. The integration of quantitative and qualitative phases compares students' and faculty's usage and attitudes toward AI and brings important insights that focus on improving the AI-using environment, ensuring sufficient financial support, and offering professional training for both faculty and students. Based on the findings, students can be guided in developing informed attitudes about AI utilization through faculty's demonstration of appropriate AI usage, fostering meaningful conversations about AI integration, and experiential learning opportunities to practice AI-assisted learning.