Learning to Diagnose with Simulations

Frank Fischer studied psychology at the Universities in Trier and Aachen, obtained a doctorate in 1997 from Ludwig Maximilian University (LMU) in Munich. After professorships in Erfurt and Tübingen, he became a full professor for educational science and educational psychology at LMU. His research focuses on digital learning, collaborative learning, scientific and diagnostic reasoning, as well as evidence-based practice in education. He served as the Director of the Department of Psychology and Dean of Faculty at LMU. He was the president of the International Society of the Learning Sciences. He has been the director of the Munich Center of the Learning Sciences, which involves researchers and their workgroups from 8 faculties who engage in interdisciplinary research projects and in international masters' and PhD programs in the learning sciences.

• 1. A theoretical framework for learning diagnostic competences with simulations.- 2. Diagnosing primary school children’s mathematical competences and misconceptions based on their written work.- 3. Diagnosing mathematical argumentation skills in secondary school based on videos of students attempting to construct proofs.- 4. Diagnosing 6th graders´ understanding of decimal fractions – A role-play-based simulation for mathematics teacher students of diagnostic interviews featuring simulated teacher-student interactions.- 5. Diagnosing the instructional quality of biology lessons based on staged-videos.- 6. Diagnosing secondary school students´ scientific reasoning skills in physics and biology – A video-based simulation for pre-service teachers.- 7. Diagnosing students’ behavioral, developmental and learning disorders based on records of behavior and performance.- 8. Facilitating Medical History Taking through Live and Computer Simulations.- 9. Learning collaborativeDiagnosing in Medical Education – Diagnosing a Patient’s Disease in Collaboration with a Simulated Radiologist.- 10. Using simulations to facilitate professional competences: promising trajectories for future research.