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A social robot as your reading companion: exploring the relationships between gaze patterns and knowledge gains

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Abstract

Intelligent tutoring systems have been widely used in educational activities over the past 20 years. With significantly less effort put into writing or reading assistance, the majority of intelligent tutoring systems focus on mathematics or problem solving activities. However, with the development of E-reading-centered E-education, how to improve students’ learning performance during reading has become increasingly important. Therefore, in this paper, we take a first step in the direction of an adaptive intelligent tutoring system by investigating how different reading strategies relate to knowledge gain based on gaze features and how an embodied social robot affects gaze patterns and reading strategies. The findings showed that different knowledge gains have significant differences in scanning methods and reading depth, and that the feedback given by social robots significantly affects participants’ gaze patterns during the whole reading process. To automatically differentiate between two levels of knowledge gain, several prediction experiments based on various reading strategy-related gaze features were carried out. The results demonstrate that saccades are the best predictors of knowledge gain, with the best model having an average accuracy of 74.2%. Finally, real-time simulation experiments were conducted with sixty participants using the leave-one-out method, and an accurate prediction of the level of knowledge gain of 71. 5% was achieved.

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Availability of data and materials

The eye gaze data that support the findings of this study are available from the Interactive Intelligence group of TU delft. The data may be available upon request but not for all due to relevant data protection laws.

Notes

  1. https://pupil-labs.com/.

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Acknowledgements

The data collection was supported by the Interactive Intelligence Group and the Web Information Systems Group at TU Delft. Additionally, the authors would like to thank Yoon Lee, Catharine Oertel, Marcus Specht, and Jennifer Olsen for their help with the work.

Funding

The first author is funded by the China Scholarship Council (CSC) (No. 202006120103) from the Ministry of Education of the P.R. China. This work was supported by the National Natural Science Foundation of China under Grant 61876054. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Authors and Affiliations

  1. Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150001, People’s Republic of China

    Xuan Liu & Qiang Wang

  2. Department of Control Science and Engineering, Harbin Institute of Technology, Weihai, 150001, People’s Republic of China

    Jiachen Ma

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XL designed and performed the experiments, derived the models and analysed the data. JM, QW, and XL interpreted the data analysis results and wrote the manuscript together. All authors of this paper have read and approved the final version submitted.

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Correspondence to Qiang Wang.

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Appendix A: Questionnaire

Appendix A: Questionnaire

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Liu, X., Ma, J. & Wang, Q. A social robot as your reading companion: exploring the relationships between gaze patterns and knowledge gains. J Multimodal User Interfaces 18, 21–41 (2024). https://doi.org/10.1007/s12193-023-00418-5

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