Computers in health care education

Biomedical Informatics: Computer Applications in Health Care and Biomedicine: Fourth Edition

Volumn , Issue , 2014, Pages 675-693

  Dev, Parvati ^a   Schleyer, Titus K L ^b  

^a Innovation in Learning Inc   (United States)

^b REGENSTRIEF INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SCIENCE; COMPUTERS;

HEALTH CARE EDUCATION;

MEDICAL COMPUTING;

EID: 84969521565     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-1-4471-4474-8_23     Document Type: Chapter

References (8)

1. AAMC Institute for Improving Medical Education. (2007, March). Washington, D. C.: American Association of Medical Colleges. https://members.aamc.org/eweb/upload/Effective%20Use%20of%20Educational.pdf Effective use of educational technology in medical education. Colloquium on educational technology: Recommendations and guidelines for medical educators. This report summarizes the discussion of an expert panel on the documented efficacy of educational technologies in the curriculum.
2. Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How people learn: Brain, mind experience and school. Washington, D.C.: The National Academies Press. This National Research Council book synthesizes many findings on the science of learning, and explains how these insights can be applied to actual practice in teaching and learning.
3. Cook, D. A. (2005). The research we still are not doing: An agenda for the study of computer-based learning. Acad Med, 80 (6), 541-548. Cook reviews the progress (or lack thereof) on Friedman's proposed directions for educational software research, and suggests strategies for meaningful comparisons in computer-based instructional design. He discusses additional research challenges, such as adaptation to individual learners, just-in time learning and simulation.
4. Crowley, R. S., Legowski, E., Medvedeva, O. M., Tseytlin, E., Roh, E., & Jukic, D. (2007). Evaluation of an Intelligent Tutoring System in Pathology: Effects of External Representation on Performance JAMIA, 14 (2), 182-190. Crowley describes a study that evaluated SlideTutor with physicians in two academic pathology programs. On average, students improved their diagnostic and reporting performance by a factor of four after as little as four hours of use of the system.
5. Eliot C. R., Woolf B. P. (1996). An intelligent learning environment for advanced cardiac life support. Proceedings of the AMIA Annual Fall Symposium, Washington, DC, pp.7-11.
6. Gaba, D. M. (2004). The future vision of simulation in health care. Qual Saf Health Care, 13 (Suppl 1), i2-i10. Gaba describes the range of technologies and methods available for simulation-based learning.
7. Kirkpatrick, D. L. (1994). Evaluating training programs. San Francisco: Berrett-Koehler. This book presents a multilevel system for evaluating training programs.
8. Rall, M., Gaba, D. M., Dieckmann, P., & Eich, C. (2010). Chapter 7: Patient simulation. In R. D. Miller (Ed.), Anesthesia (7th ed.). Philadelphia: Churchill Livingstone Elsevier. The authors summarize the history and current uses of manikin-based simulation, the most common type of simulation in use for clinical teaching.