Nonlinear dynamics research of eye-tracking data in MOOC video learning

Journal Title: Journal of Air Force Medical University - Year 2023, Vol 44, Issue 5

Abstract

Objective To explore the nonlinear dynamics characteristics of eye-tracking data in MOOC video learning. Methods In this study, the sliding window permutation entropy of pupil diameter was calculated, and the obtained permutation entropy sequence was analyzed by wavelet scalogram and power spectrum. The peak frequency values of power spectrum were converted into the corresponding peak periods. Results The analysis of wavelet scalogram showed that the absolute value of the wavelet coefficients had a strong component in the range of 0. 010 - 0. 025 Hz. The peak period of the power spectrum was normally distributed, with a mean of 81. 38 s. Conclusion The sliding window permutation entropy can monitor pupil changes in real time during MOOC learning, extract vigilance-related features, and provide technical support for the development of adaptive e-learning.

Authors and Affiliations

XIE Kangning, LI Yan, DU Junjie, WU Xiaoming, JING Da, LIU Juan, ZHAI Mingming, LU Hongbing, TANG Chi,LUO Erping

Keywords

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  • EP ID EP727768
  • DOI -
  • Views 47
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How To Cite

XIE Kangning, LI Yan, DU Junjie, WU Xiaoming, JING Da, LIU Juan, ZHAI Mingming, LU Hongbing, TANG Chi, LUO Erping (2023). Nonlinear dynamics research of eye-tracking data in MOOC video learning. Journal of Air Force Medical University, 44(5), -. https://europub.co.uk/articles/-A-727768