2D 메타버스 아바타 트레이싱의 학습역량 제고 효과의 실험

다국어 초록 (Multilingual Abstract)

This study explored the potential of 2D metaverse avatar navigation for tracing-based learning. An online experiment was conducted with a lesson comparing three loan repayment schedules by tracing/reading bar graphs; the lesson is presented in four conditions differing in information length (‘Short/Long’) and learning method (‘Tracing/Reading’). Participants were randomly assigned to one of the four learning conditions, then completed a questionnaire measuring the effects of tracing in improving comprehension scores and reducing extraneous cognitive load; later they tried both tracing and reading to choose their preferred method and to comment on why. Comprehension scores were significantly improved in the Short-Tracing group where participants solved transfer questions requiring higher cognitive effort. However, the cognitive load of the Short-Tracing group was higher than that of the Short-Reading group and as high as that of the Long-Tracing group. Avatar tracing was preferred for interestingness in both the Short and Long groups, but only preferred for comprehensibility in the Short group. The proportion of participants who preferred tracing to reading for all aspects of comprehensibility, engagement, and interestingness was significantly higher in the Short group, suggesting that the effectiveness of avatar tracing is influenced by the length of information and the difficulty of the test. Participants commented that avatar tracing supported comprehension through • sensorimotor experience, • embodied learning leading to better memory, • improved visual attention; engagement through • active participation; and interest through its novelty. However, the keyboard operation of avatar tracing was too tedious if the shape to be traced was too complicated and long. The findings suggest that avatar tracing-based learning has the potential to engage learners and help them understand better if the lesson is designed with length and complexity in mind.