SlideTutor: A model-tracing Intelligent Tutoring System for teaching pathologic diagnosis

We report on initial system development of SlideTutor a web-deployed, image-based, model-tracing Intelligent Tutoring System for teaching microscopic diagnosis. The system is based on our previous work describing the development of expertise in this complex visual diagnostic task. SlideTutor is designed to provide individualized coaching to students as they search, and interpret virtual pathology slides. The system models three important sets of cognitive skills: slide search and lesion detection, visual feature identification, and diagnostic inference. We describe the design and development of the model-tracer for this system, including system architecture, knowledge representation, methods for feedback, and student interface. SlideTutor: A model-tracing Intelligent Tutoring System for teaching microscopic diagnosis REBECCA CROWLEY, OLGA MEDVEDEVA and DRAZEN JUKIC Center for Pathology Informatics, and Departments of Pathology and Dermatology University of Pittsburgh School of Medicine [email protected] Abstract. We report on initial system development of SlideTutor a web-deployed, image-based, model-tracing Intelligent Tutoring System for teaching microscopic diagnosis. The system is based on our previous work describing the development of expertise in this complex visual diagnostic task. SlideTutor is designed to provide individualized coaching to students as they search, and interpret virtual pathology slides. The system models three important sets of cognitive skills: slide search and lesion detection, visual feature identification, and diagnostic inference. We describe the design and development of the model-tracer for this system, including system architecture, knowledge representation, methods for feedback, and student interface. We report on initial system development of SlideTutor a web-deployed, image-based, model-tracing Intelligent Tutoring System for teaching microscopic diagnosis. The system is based on our previous work describing the development of expertise in this complex visual diagnostic task. SlideTutor is designed to provide individualized coaching to students as they search, and interpret virtual pathology slides. The system models three important sets of cognitive skills: slide search and lesion detection, visual feature identification, and diagnostic inference. We describe the design and development of the model-tracer for this system, including system architecture, knowledge representation, methods for feedback, and student interface.