Preliminary insights into dental student satisfaction in flippedclassroom seminars enhanced by artificial intelligence-generated podcasts: a comparative study.

AIM: To evaluate the perceived usefulness of a flipped-classroom model that integrated podcasts generated using an artificial intelligence (AI) tool in undergraduate dental education. MATERIALS AND METHODS: The present within-subject, quasi-experimental study was conducted at a Swiss dental school. A cohort of 49 clinical-year dental students participated in eight conventional seminars and two flipped-classroom seminars, each covering a distinct clinical topic. In both formats, a subset of five or six students acted as instructors under the supervision of residents or faculty members. The flipped-classroom model required students to engage with AI-generated podcast summaries of research articles before in-class discussions. These podcasts were created using NotebookLM, an online platform powered by a large language model. Surveys using Likert-type scales assessed student and student instructor satisfaction, engagement, and learning preferences. RESULTS: The surveys obtained response rates of ≥ 93.9%. The flipped-classroom model achieved high satisfaction levels among students. Compared with conventional seminars, students reported increased engagement and comprehension in the flipped-classroom format. Student instructors valued the ease of preparation and the enhanced interactivity of in-class sessions. AI-generated podcasts were rated as effective pre-class resources. CONCLUSIONS: The integration of a flipped-classroom model with AI-generated podcast resources seemed to improve student self-perception of engagement, comprehension, and satisfaction in dental education. This instructional approach may also foster critical appraisal skills for AI-generated content-an increasingly essential competence in academic and professional practice as AI tools gain prominence.