The superiority of three‐dimensional physical models to two‐dimensional computer presentations in anatomy learning

摘要

Background Although several studies ( Anat Sci Educ , 8 [6], 525, 2015) have shown that computer‐based anatomy programs (three‐dimensional visualisation technology [3 DVT ]) are inferior to ordinary physical models ( PM s), the mechanism is not clear. In this study, we explored three mechanisms: haptic feedback, transfer‐appropriate processing and stereoscopic vision. Methods The test of these hypotheses required nine groups of 20 students: two from a previous study ( Anat Sci Educ , 6 [4], 211, 2013) and seven new groups. (i) To explore haptic feedback from physical models, participants in one group were allowed to touch the model during learning; in the other group, they could not; (ii) to test ‘transfer‐appropriate processing’ ( TAP ), learning ( PM or 3 DVT ) was crossed with testing (cadaver or two‐dimensional display of cadaver); (iii) finally, to examine the role of stereo vision, we tested groups who had the non‐dominant eye covered during learning and testing, during learning, or not at all, on both PM and 3 DVT . The test was a 15‐item short‐answer test requiring naming structures on a cadaver pelvis. A list of names was provided. Results The test of haptic feedback showed a large advantage of the PM over 3 DVT regardless of whether or not participants had haptic feedback: 67% correct for the PM with haptic feedback, 69% for PM without haptic feedback, versus 41% for 3 DVT (p??0.0001). In the study of TAP , the PM had an average score of 74% versus 43% for 3 DVT (p??0.0001) regardless of two‐dimensional versus three‐dimensional test outcome. The third study showed that the large advantage of the PM over 3 DVT (28%) with binocular vision nearly disappeared (5%) when the non‐dominant eye was covered for both learning and testing. Conclusions A physical model is superior to a computer projection, primarily as a consequence of stereoscopic vision with the PM . The results have implications for the use of digital technology in spatial learning.