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Development of Kanji Learning Materials for Dysgraphia and EEG Measurement

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Computer Science and Education. Computer Science and Technology (ICCSE 2023)

Abstract

The primary aim of the research project is to develop instructional materials for Kanji learning, specifically targeting students facing difficulties or disabilities in writing. The effectiveness of traditional methods, emphasizing extensive reading and extensive handwriting to enhance brain working memory, has been questioned due to significant accumulations of fatigue and stress revealed in EEG results. To address these concerns, an innovative approach is proposed, focusing on the efficient development of a method to train the brain’s working memory in Kanji learning, heightened by increased awareness of spatial cognition. This method is implemented in high schools and universities, with subsequent measurement of its effects. Iterative improvements is made based on the school feedback and the effectiveness assessments, including enlarging character size and enhancing spatial cognition skills associated with characters to optimize the efficacy of character learning. In this study, we introduce an evaluation of the proposed educational method by the measurement of rhythms in the Electroencephalograms (EEGs).

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References

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Acknowledgment

This study was supported in part by the Whiterock Foundation and JSPS KAKENHI Grant Numbers 23H03678.

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Correspondence to Kenichiro Kutsuna .

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Kutsuna, K., Somchanakit, K., Teppradit, C., Nilaubol, P., Rongdech, C., Takada, H. (2024). Development of Kanji Learning Materials for Dysgraphia and EEG Measurement. In: Hong, W., Kanaparan, G. (eds) Computer Science and Education. Computer Science and Technology. ICCSE 2023. Communications in Computer and Information Science, vol 2023. Springer, Singapore. https://doi.org/10.1007/978-981-97-0730-0_41

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  • DOI: https://doi.org/10.1007/978-981-97-0730-0_41

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-0729-4

  • Online ISBN: 978-981-97-0730-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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