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Learning Performance with Interactive Simulations in Medical Education: Lessons Learned from Results of Learning Complex Physiological Models with the HAEMOdynamics SIMulator

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Title: Learning Performance with Interactive Simulations in Medical Education: Lessons Learned from Results of Learning Complex Physiological Models with the HAEMOdynamics SIMulator
Language: English
Authors: Holzinger, Andreas, Kickmeier-Rust, Michael D., Wassertheurer, Sigi
Source: Computers & Education. Feb 2009 52(2):292-301.
Availability: Elsevier. 6277 Sea Harbor Drive, Orlando, FL 32887-4800. Tel: 877-839-7126; Tel: 407-345-4020; Fax: 407-363-1354; e-mail: usjcs@elsevier.com; Web site: http://www.elsevier.com
Peer Reviewed: Y
Physical Description: PDF
Page Count: 10
Publication Date: 2009
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Physiology, Learning Theories, Medical Education, Medical Students, Educational Theories, Psychology, Cognitive Processes, Computer Software Evaluation, Educational Technology, Computer Simulation, Computer Software, Instructional Design, Teaching Methods, Instructional Effectiveness, Quasiexperimental Design
DOI: 10.1016/j.compedu.2008.08.008
ISSN: 0360-1315
Abstract: Objective: Since simulations are often accepted uncritically, with excessive emphasis being placed on technological sophistication at the expense of underlying psychological and educational theories, we evaluated the learning performance of simulation software, in order to gain insight into the proper use of simulations for application in medical education. Design: The authors designed and evaluated a software packet, following of user-centered development, which they call Haemodynamics Simulator (HAEMOSIM), for the simulation of complex physiological models, e.g., the modeling of arterial blood flow dependent on the pressure gradient, radius and bifurcations; shear-stress and blood flow profiles depending on viscosity and radius. Measurements: In a quasi-experimental real-life setup, the authors compared the learning performance of 96 medical students for three conditions: (1) conventional text-based lesson; (2) HAEMOSIM alone and (3) HAEMOSIM with a combination of additional material and support, found necessary during user-centered development. The individual student's learning time was unvarying in all three conditions. Results: While the first two settings produced equivalent results, the combination of additional support and HAEMOSIM yielded a significantly higher learning performance. These results are discussed regarding Mayer's multimedia learning theory, Sweller's cognitive load theory, and claims of prior research on utilizing interactive simulations for learning. Conclusion: The results showed that simulations can be beneficial for learning complex concepts, however, interacting with sophisticated simulations strain the limitation of cognitive processes; therefore successful application of simulations require careful "additional guidance" from medical professionals and a certain amount of "previous knowledge" on the part of the learners. The inclusion of pedagogical and psychological expertise into the design and development of educational software is essential. (Contains 2 tables and 4 figures.)
Abstractor: As Provided
Entry Date: 2009
Accession Number: EJ823134
Database: ERIC
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  Data: Learning Performance with Interactive Simulations in Medical Education: Lessons Learned from Results of Learning Complex Physiological Models with the HAEMOdynamics SIMulator
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  Data: Elsevier. 6277 Sea Harbor Drive, Orlando, FL 32887-4800. Tel: 877-839-7126; Tel: 407-345-4020; Fax: 407-363-1354; e-mail: usjcs@elsevier.com; Web site: http://www.elsevier.com
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  Data: 10.1016/j.compedu.2008.08.008
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  Data: Objective: Since simulations are often accepted uncritically, with excessive emphasis being placed on technological sophistication at the expense of underlying psychological and educational theories, we evaluated the learning performance of simulation software, in order to gain insight into the proper use of simulations for application in medical education. Design: The authors designed and evaluated a software packet, following of user-centered development, which they call Haemodynamics Simulator (HAEMOSIM), for the simulation of complex physiological models, e.g., the modeling of arterial blood flow dependent on the pressure gradient, radius and bifurcations; shear-stress and blood flow profiles depending on viscosity and radius. Measurements: In a quasi-experimental real-life setup, the authors compared the learning performance of 96 medical students for three conditions: (1) conventional text-based lesson; (2) HAEMOSIM alone and (3) HAEMOSIM with a combination of additional material and support, found necessary during user-centered development. The individual student's learning time was unvarying in all three conditions. Results: While the first two settings produced equivalent results, the combination of additional support and HAEMOSIM yielded a significantly higher learning performance. These results are discussed regarding Mayer's multimedia learning theory, Sweller's cognitive load theory, and claims of prior research on utilizing interactive simulations for learning. Conclusion: The results showed that simulations can be beneficial for learning complex concepts, however, interacting with sophisticated simulations strain the limitation of cognitive processes; therefore successful application of simulations require careful "additional guidance" from medical professionals and a certain amount of "previous knowledge" on the part of the learners. The inclusion of pedagogical and psychological expertise into the design and development of educational software is essential. (Contains 2 tables and 4 figures.)
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      – SubjectFull: Learning Theories
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      – SubjectFull: Medical Education
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      – SubjectFull: Medical Students
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      – SubjectFull: Quasiexperimental Design
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      – TitleFull: Learning Performance with Interactive Simulations in Medical Education: Lessons Learned from Results of Learning Complex Physiological Models with the HAEMOdynamics SIMulator
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