Learning Model to Achieve Clinical Reasoning Competency Using Technology-Enhanced Learning in Neurology Clinical Rotation: An Exploratory Study

Abstract

The COVID-19 pandemic has necessitated major adaptations in learning activities related to developing clinical reasoning competencies in neurology clerkship. The application of technology in this context is promising, but there are also several limitations. This study explores a learning model for achieving clinical reasoning competency using technology-enhanced learning in neurology clinical rotation. The study used a case-study design and was conducted at the Faculty of Medicine of YARSI University and its two teaching hospitals. Data were collected by document analysis, three focus group discussions with eight medical students and 20 postgraduate medical students, and five in-depth interviews with five neurologists. All the transcribed data were analysed with thematic analysis using the Steps for Coding and Theorization (SCAT) approach. Two themes were revealed—contributing factors and learning strategies—and six factors were found to influence the learning model: the quantity and quality of teacher interactions, students’ motivation and skills in learning and technology, the variety and number of patients in teaching hospitals, the quality and quantity of facilities and infrastructure for service and education at the teaching hospitals, the clinical rotation programme design, and learning adaptation during the pandemic. The following technology-enhanced learning strategies for developing clinical reasoning skills were identified: blended learning, online logbook, telemedicine, collaborative online learning between teaching hospitals, and learning videos. This learning model can be implemented in a limited resource setting. Importantly, the identified factors from the perspective of students, clinical teachers, and school of medicine/teaching hospital, as well as technical factors, should be considered for the implementation of this model.