The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
The relative effectiveness of computer‐based and traditional resources for education in anatomy
Abstract
There is increasing use of computer–based resources to teach anatomy, although no study has compared computer‐based learning to traditional. In this study, we examine the effectiveness of three formats of anatomy learning: (1) a virtual reality (VR) computer‐based module, (2) a static computer‐based module providing Key Views (KV), (3) a plastic model. We conducted a controlled trial in which 60 undergraduate students had ten minutes to study the names of 20 different pelvic structures. The outcome measure was a 25 item short answer test consisting of 15 nominal and 10 functional questions, based on a cadaveric pelvis. All subjects also took a brief mental rotations test (MRT) as a measure of spatial ability, used as a covariate in the analysis. Data were analyzed with repeated measures ANOVA. The group learning from the model performed significantly better than the other two groups on the nominal questions (Model 67%; KV 40%; VR 41%, Effect size 1.19 and 1.29, respectively). There was no difference between the KV and VR groups. There was no difference between the groups on the functional questions (Model 28%; KV, 23%, VR 25%). Computer‐based learning resources appear to have significant disadvantages compared to traditional specimens in learning nominal anatomy. Consistent with previous research, virtual reality shows no advantage over static presentation of key views. Anat Sci Educ 6: 211–215. © 2013 American Association of Anatomists.
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Cites
Mental Rotations, a Group Test of Three-Dimensional Spatial Visualization
Vandenberg, S. G., & Kuse, A. R. (1978) · Perceptual and Motor Skills · doi:10.2466/pms.1978.47.2.599 · Cited by 2,620
Cook, D. A., Hatala, R., Brydges, R., Zendejas, B., Szostek, J. H., Wang, A. T., Erwin, P. J., & Hamstra, S. J. (2011) · JAMA · doi:10.1001/jama.2011.1234 · Cited by 2,170
Cognitive load theory in health professional education: design principles and strategies
Van Merriënboer, J. J. G., & Sweller, J. (2010) · Medical Education · doi:10.1111/j.1365-2923.2009.03498.x · Cited by 1,511
Internet-Based Learning in the Health Professions: A Meta-analysis
Cook, D. A., Levinson, A. J., Garside, S., Dupras, D. M., Erwin, P. J., & Montori, V. M. (2008) · JAMA · doi:10.1001/jama.300.10.1181 · Cited by 1,498
The anatomy of anatomy: A review for its modernization
Sugand, K., Abrahams, P., & Khurana, A. (2010) · Anatomical Sciences Education · doi:10.1002/ase.139 · Cited by 991
Teaching anatomy without cadavers
McLachlan, J. C., Bligh, J., Bradley, P., & Searle, J. (2004) · Medical Education · doi:10.1046/j.1365-2923.2004.01795.x · Cited by 602
Computerized Virtual Patients in Health Professions Education: A Systematic Review and Meta-Analysis
Cook, D. A., Erwin, P. J., & Triola, M. M. (2010) · Academic Medicine · doi:10.1097/acm.0b013e3181edfe13 · Cited by 570
DeLeeuw, K. E., & Mayer, R. E. (2008) · Journal of Educational Psychology · doi:10.1037/0022-0663.100.1.223 · Cited by 558
Anatomical dissection as a teaching method in medical school: a review of the evidence
Winkelmann, A. (2007) · Medical Education · doi:10.1111/j.1365-2929.2006.02625.x · Cited by 411
Preece, D., Williams, S. B., Lam, R., & Weller, R. (2013) · Anatomical Sciences Education · doi:10.1002/ase.1345 · Cited by 409
How medical students learn spatial anatomy
Garg, A. X., Norman, G., & Sperotable, L. (2001) · The Lancet · doi:10.1016/s0140-6736(00)03649-7 · Cited by 351
Self-citationIs the gender difference in mental rotation disappearing?
Masters, M. S., & Sanders, B. (1993) · Behavior Genetics · doi:10.1007/bf01067434 · Cited by 338
How Are Three-Dimensional Objects Represented in the Brain?
Bulthoff, H. H., Edelman, S. Y., & Tarr, M. J. (1995) · Cerebral Cortex · doi:10.1093/cercor/5.3.247 · Cited by 296
Web‐based interactive 3D visualization as a tool for improved anatomy learning
Petersson, H., Sinkvist, D., Wang, C., & Smedby, Ö. (2009) · Anatomical Sciences Education · doi:10.1002/ase.76 · Cited by 268
Anatomy 1999–2000: the curriculum, who teaches it and how?
Heylings, D. J. A. (2002) · Medical Education · doi:10.1046/j.1365-2923.2002.01272.x · Cited by 259
Medical students' learning of anatomy: memorisation, understanding and visualisation
Pandey, P., & Zimitat, C. (2007) · Medical Education · doi:10.1111/j.1365-2929.2006.02643.x · Cited by 241
Relationship Between Spatial Abilities, Mental Rotation and Functional Anatomy Learning
Guillot, A., Champely, S., Batier, C., Thiriet, P., & Collet, C. (2007) · Advances in Health Sciences Education · doi:10.1007/s10459-006-9021-7 · Cited by 223
Virtual reality and brain anatomy: a randomised trial of e‐learning instructional designs
Levinson, A. J., Weaver, B., Garside, S., McGinn, H., & Norman, G. R. (2007) · Medical Education · doi:10.1111/j.1365-2929.2006.02694.x · Cited by 205
Self-citationGARG, A. X., NORMAN, G. R., EVA, K. W., SPERO, L., & SHARAN, S. (2002) · Academic Medicine · doi:10.1097/00001888-200210001-00030 · Cited by 184
Self-citationDo virtual computer models hinder anatomy learning?
Garg, A., Norman, G. R., Spero, L., & Maheshwari, P. (1999) · Academic Medicine · doi:10.1097/00001888-199910000-00049 · Cited by 183 · cited 6×
“Indeed, what studies have been done have generally shown that digital enhancements, like virtual reality (VR) or dynamic presentations, are as likely to lead to negative as positive effects (Garg et al., 1999, 2001, 2002; Levinson, 2007).”
BackgroundResultInfluentialSelf-citationSex differences and the factor of time in solving Vandenberg and Kuse mental rotation problems
Peters, M. (2005) · Brain and Cognition · doi:10.1016/j.bandc.2004.08.052 · Cited by 172
Effect of visual–spatial ability on medical students' performance in a gross anatomy course
Lufler, R. S., Zumwalt, A. C., Romney, C. A., & Hoagland, T. M. (2012) · Anatomical Sciences Education · doi:10.1002/ase.264 · Cited by 169
Evaluation of computer‐aided instruction in a gross anatomy course: A six‐year study
McNulty, J. A., Sonntag, B., & Sinacore, J. M. (2009) · Anatomical Sciences Education · doi:10.1002/ase.66 · Cited by 166
Spatial learning disabilities and underachievement among university anatomy students
ROCHFORD, K. (1985) · Medical Education · doi:10.1111/j.1365-2923.1985.tb01134.x · Cited by 159
The Effects of Sex, Sexual Orientation, and Digit Ratio (2D:4D) on Mental Rotation Performance
Peters, M., Manning, J. T., & Reimers, S. (2007) · Archives of Sexual Behavior · doi:10.1007/s10508-006-9166-8 · Cited by 158
Enhancement of Mental Rotation Abilities and Its Effect on Anatomy Learning
Hoyek, N., Collet, C., Rastello, O., Fargier, P., Thiriet, P., & Guillot, A. (2009) · Teaching and Learning in Medicine · doi:10.1080/10401330903014178 · Cited by 146
Diffusion of innovations: Smartphones and wireless anatomy learning resources
Trelease, R. B. (2008) · Anatomical Sciences Education · doi:10.1002/ase.58 · Cited by 134
Is learning anatomy facilitated by computer-aided learning? A review of the literature
Tam, M. D. B. S., Hart, A. R., Williams, S., Heylings, D. J., & Leinster, S. (2009) · Medical Teacher · doi:10.1080/01421590802650092 · Cited by 123
Getting a handle on learning anatomy with interactive three-dimensional graphics.
Stull, A. T., Hegarty, M., & Mayer, R. E. (2009) · Journal of Educational Psychology · doi:10.1037/a0016849 · Cited by 92
A head in virtual reality: Development of a dynamic head and neck model
Nguyen, N. T. T., & Wilson, T. D. (2009) · Anatomical Sciences Education · doi:10.1002/ase.115 · Cited by 63
Teaching bovine abdominal anatomy: Use of a haptic simulator
Kinnison, T., Forrest, N. D., Frean, S. P., & Baillie, S. (2009) · Anatomical Sciences Education · doi:10.1002/ase.109 · Cited by 59
Cited by
Zhao, J., Xu, X., Jiang, H., & Ding, Y. (2020) · BMC Medical Education · doi:10.1186/s12909-020-1994-z · Cited by 445
Iwanaga, J., Loukas, M., Dumont, A. S., & Tubbs, R. S. (2021) · Clinical Anatomy · doi:10.1002/ca.23655 · Cited by 328
Trelease, R. B. (2016) · Anatomical Sciences Education · doi:10.1002/ase.1620 · Cited by 266
Metadata
- Authors
- Khot, Z., Quinlan, K., Norman, G. R., & Wainman, B.
- Venue
- Anatomical Sciences Education
- Publisher
- Wiley
- Published
- 2013-03-18
- Volume
- 6
- Issue
- 4
- Pages
- 211-215
- ISSN
- 1935-9772 (ISSN-L)
- 1935-9780
- OpenAlex
- W1529289001
- Cited by
- 274
- References
- 31
- FWCI
- 6.38
- Type
- journal article
- Language
- en
- Open access
- closed
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