Investigating Generative AI Utilization for Project-Based Learning: Teachers’ Role, Challenges, and Strategies in Higher Education

Fitriyah Fitriyah, Ratnawati Ratnawati

Abstract


Despite growing interest in generative Artificial Intelligence (GenAI) in educational technologies, limited research has explored how it specifically affects pedagogical practices in a project-based learning (PjBL) atmosphere. This study investigates how university teachers utilize GenAI in PjBL, emphasizing their roles, challenges faced, and the strategies they employed during classroom practices. The study adopted a convergent mixed-methods approach, which involved a quantitative survey of 63 university teachers and qualitative interviews with six selected participants to gain deeper insights. The findings revealed that teachers play a central role in guiding students’ use of GenAI tools as evidenced by M (3.67) and SD (0.72), acting as facilitators, instructional designers,  and ethical gatekeepers. While GenAI is increasingly incorporated for tasks such as brainstorming, drafting, and feedback in student projects, the use of GenAI in PjBL raises several pedagogical and institutional challenges. Key concerns faced challenges were varying levels of digital and AI literacy among teachers, difficulties in assessing AI-generated work, and a lack of clear policies. Additionally, the study highlighted actionable strategies for structured support systems and professional development to enhance teachers’ confidence and competence in using GenAI tools effectively and ethically, such as embedding AI literacy into faculty training, developing assessment frameworks adapted to AI-enhanced learning, and promoting reflective use of GenAI in collaborative settings. This research contributes to the understanding of how teachers navigate emerging technologies and offers guidance for institutions aiming to align GenAI integration with pedagogically sound and ethically responsible practices in higher education. 

Keywords


Artificial Intelligence, Generative AI, Higher Education, Project-based learning

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DOI: http://dx.doi.org/10.25157/jwp.v12i2.19776

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