289 A Problem-Based Learning Platform for Advanced Dermatopathology Education: Development and Comparative Evaluation

Introduction/Objective The increasing global burden of cutaneous malignancies necessitates enhanced educational methodologies to support early diagnostic accuracy and informed clinical decision-making. We present DermaIntel, a novel problem-based learning (PBL) platform specifically designed for advanced dermatopathology training. The system integrates case-driven modules, individualized content delivery, and continuously updated peer-reviewed literature to address evolving educational demands in dermatopathology. Methods/Case Report Development followed a six-phase translational framework. First, core training materials were curated from authoritative sources, including Atlas of Dermatopathology: Synopsis and Lever’s Histopathology of the Skin, Fourth Edition. Second, educational logic was developed using structured clinical reasoning pathways and expert-vetted content to ensure contextual accuracy. Third, a real-time literature integration protocol was implemented to ensure current and evidence-based instructional content. Fourth, a user-centric interface was designed to support scenario-based engagement and structured inquiry. Fifth, educational efficacy was assessed through targeted evaluations involving pathology trainees and practicing dermatopathologists. Finally, performance metrics were captured using embedded analytic modules to track learning outcomes, retention, and user interaction patterns. Results The platform includes stratified case-based tutorials and interactive Q&A sessions calibrated to the user’s experience level. Its use of Socratic dialogue structures promotes critical thinking, diagnostic synthesis, and long-term retention. Compared with existing dermatopathology educational platforms (e.g., PathPresenter, static slide atlases), DermaIntel demonstrated superior adaptability, learner engagement, content relevance, and guideline alignment. A comparative radar chart summarizes its performance across six domains: education accuracy support, instructional adaptability, user engagement, clinical guideline integration, delivery efficiency, and continuous knowledge updates. Conclusion In conclusion, DermaIntel represents a structured, evidence-informed educational platform that responds to unmet needs in dermatopathology training. Its dynamic content structure and interactive pedagogical approach position it as a valuable adjunct to traditional pathology education. Future development will explore the integration of clinical metadata and user-generated diagnostic inputs to further enhance personalization and educational impact.