Effects of Attention Level and Learning Style Based on Electroencephalo-Graph Analysis for Learning Behavior in Immersive Virtual Reality

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Abstract

Immersive virtual reality technology (IVR) can create contextualized learning environments that learners cannot easily access. It is widely used in education. More and more researchers are paying attention to IVR's influencing factors. However, most of these researches focus on the aspects of technology and environment, ignoring the aspects of learners themselves. Therefore, this paper explores the impact of learners' attention level (AL) and learning style (LS) on learning behavior in IVR. Firstly, the AL data monitored by EEG equipment allows correlation and difference analysis to explore the relationship among AL, LS and learning performance (LP). Then, according to the video-recorded learning behavior data, the lag sequence analysis method is used to analyze the learning behavior sequence transformation of the high-concentration group and low-concentration group so that it can explore the problem learning behaviors of learners with different concentrations. The results show that: in the virtual learning environment (Vir-LE), there is a strong positive correlation between AL and LP. There is no significant difference in LP with different LS, but the AL of visual learners is higher than that of verbal learners. Through this experiment, it is helpful to eliminate the interference factors in the range of human subjective perception and improve the accuracy of the measurement of learning effect.

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Cao, L., He, M., & Wang, H. (2023). Effects of Attention Level and Learning Style Based on Electroencephalo-Graph Analysis for Learning Behavior in Immersive Virtual Reality. IEEE Access, 11, 53429–53438. https://doi.org/10.1109/ACCESS.2023.3280631

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