THE ROLE OF GENERATIVE AI-POWERED PERSONAS IN DEVELOPING GRADUATE INTERVIEWING SKILLS
Soroush Sabbaghan, BARBARA J. BROWN · International journal on innovations in online education · 2024
This article presents an in-depth examination of the artificial intelligence (AI)-powered persona-generating program PEARL-Persona Emulating Adaptive Research and Learning Bot, which utilizes GPT-4 application programming interface (API), for developing graduate students' research-interview skills. PEARL offers a novel solution to the challenges faced in qualitative research, such as ethical concerns, participant accessibility, and data diversity, by simulating realistic personas for interview training. This study, framed by experiential learning theory (ELT), explores graduate students' experiences with PEARL in a graduate course, focusing on how it enhances the four facets of ELT: concrete experience, reflective observation, abstract conceptualization, and active experimentation. The findings reveal that while students perceive PEARL as a beneficial tool for experiential learning and skill development, it also has limitations in replicating the complexity of human interactions. The study contributes valuable insights into the integration of generative AI in enhancing graduate research competencies and underscores the enduring need for human involvement in the research process. It highlights the potential of generative AI tools like PEARL to bridge the gap between theoretical knowledge and practical skills in graduate education, while also drawing attention to areas for future refinement and ethical considerations in generative AI-enabled pedagogy.