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Learning Science in Immersive Virtual Reality

delete2018-08-01
delete515
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OA
AI
J
Jocelyn Parong *
R
Richard E. Mayer
DOI:10.1037/edu0000241delete
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摘要

摘要

En 中文
The goals of the study were (a) to compare the instructional effectiveness of immersive virtual reality (VR) versus a desktop slideshow as media for teaching scientific knowledge, and (b) to examine the efficacy of adding a generative learning strategy to a VR lesson. In Experiment 1, college students viewed a biology lesson about how the human body works either in immersive VR or via a self-directed PowerPoint slideshow on a desktop computer. Based on interest theory, it was predicted that students who learned in immersive VR would report more positive ratings of interest and motivation and would score higher on a posttest covering material in the lesson. In contrast, based on the cognitive theory of multimedia learning, it was predicted that students who learned with a well-designed slideshow would score higher on a posttest, although they might not report higher levels of interest and motivation. The results showed that students who viewed the slideshow performed significantly better on the posttest than the VR group, but reported lower motivation, interest, and engagement ratings. In Experiment 2, students either viewed a segmented VR lesson and produced a written summary after each segment or viewed the original, continuous VR lesson as in Experiment 1. Students who summarized the lesson after each segment performed significantly better on the posttest and the groups did not differ on reported interest, engagement, and motivation. These results support the cognitive theory of multimedia learning and demonstrate the value of generative learning strategies in immersive VR environments.
Keyword:
Virtual reality
multimedia learning
summarizing
science simulation
learning strategies

期刊

Journal of Educational Psychology 封面图
Journal of Educational Psychology
IF:
6.4
论文数:
4.2K
被引数:
2.2W

机构

University of California System 封面图
University of California System
学者数:
37.5W
论文数: 33.7W
被引数: 6.6K
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