Google NotebookLM-Based AI-Augmented Interactive Lecture Model (AI-AILM): A Pilot Evaluation of an Innovative Approach

<div class="wpabstracts panel-body"><div class="wpabstracts form-group"><label class="wpabstracts control-label">Başlık</label>Google NotebookLM-Based AI-Augmented Interactive Lecture Model (AI-AILM): A Pilot Evaluation of an Innovative Approach</div><div class="wpabstracts form-group"><label class="wpabstracts control-label">Açıklama</label> <b>Purpose:</b> This study aims to evaluate the pilot implementation and student satisfaction of the "AI-Augmented Interactive Lecture Model (AI-AILM)". The model was developed to address the learning needs of Generation Z medical students and enhance the integration of evidence-based medicine (EBM) sources, such as UpToDate and ClinicalKey, into the curriculum. <b>Method:</b> This descriptive pilot study was conducted with <b>fourth-year</b> medical students (n=29) at Kocaeli University Faculty of Medicine. The AI-AILM model consists of three stages: (1) Commencing the lecture with an audio summary synthesized by Google NotebookLM from lecture notes and EBM sources; <b>This audio format was preferred due to the current limitations of the platform's video synthesis capabilities.</b> (2) An interactive discussion section led by the faculty member, highlighting critical points and utilizing AI-generated test questions. (3) Sharing the original EBM sources with students post-lecture for reinforcement. Student perception and satisfaction were assessed via an anonymous <b>five-point</b> Likert scale survey with open-ended questions. <b>Results:</b> According to responses from the 29 students, the highest-rated aspect of the model was the "synthesis of current EBM resources (UpToDate/ClinicalKey)" (<b>mean</b>: 4.38/5.0). This was followed by the "Interactive Q&amp;A session" (<b>mean</b>: 4.28/5.0) and "Faculty insights and emphasis" (<b>mean</b>: 4.17/5.0). A majority of participants (62%, n=18) perceived the use of AI as "supportive and enhancing" of the faculty member's role. In qualitative feedback, students praised the model's ability to simplify complex topics; however, the most frequently cited area for improvement was the need for visual aids (e.g., slides) during the audio summary to maintain focus. <b>Conclusion:</b> <b>AI-AILM</b> is evaluated as a successful pedagogical <b>initiative</b> with high student satisfaction, positioning AI as a "knowledge synthesizer" and the faculty as an "interaction facilitator" and "clinical guide." The findings suggest that AI integration in medical education does not substitute the faculty's role but rather enhances it, enabling more time for interactive discussions enriched by EBM resources. <b>Keywords:</b> Medical Education, Generative Artificial Intelligence, Google NotebookLM, AI-AILM, Personal Satisfaction </div></div> <br>