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Integrative Case-Based Applied Pathology (ICAP) cases form one component of learning and understanding the role of pathology in the veterinary diagnostic process at the Faculty of Veterinary Science, University of Sydney. It is a strategy that focuses on student-centered learning in a problem-solving context in the year 3 curriculum. Learning exercises use real case material and are primarily delivered online, providing flexibility for students with differing learning needs, who are supported by online, peer, and tutor support. The strategy relies heavily on the integration of pre-clinical and para-clinical information with the introduction of clinical material for the purposes of a logical three-level, problem-oriented approach to the diagnosis of disease. The focus is on logical diagnostic problem solving, primarily using gross pathology and histopathological material, with the inclusion of microbiological, parasitological, and clinical pathological data. The ICAP approach is linked to and congruent with the problem-oriented approach adopted in veterinary medicine and the case-based format used by one of the authors (PJC) for the teaching and learning of veterinary clinical pathology in year 4. Additionally, final-year students have the opportunity, during a diagnostic pathology rotation, to assist in the development and refinement of further ICAPs, which reinforces the importance of pathology in the veterinary diagnostic process. Evidence of the impact of the ICAP approach, based primarily on student surveys and staff peer feedback collected over five years, shows that discipline-specific learning, vertical and horizontal integration, alignment of learning outcomes and assessment, and both veterinary and generic graduate attributes were enhanced. Areas for improvement were identified in the approach, most specifically related to assistance in the development of generic teamwork skills.

Integrated Case-Based Applied Pathology (ICAP): A Diagnostic-Approach Model for the Learning and Teaching of Veterinary Pathology