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Inference of Learning Creative Characteristics by Analysis of EEG Signal

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Emerging Technologies for Education (SETE 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10676))

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Abstract

In recent years, more and more researches on evaluating student’s creativity has been discussed in the field of science and technology education. According to the past research results, we can find more alpha wave among electroencephalogram signals from the high creative students. In other words, the process of generating creative ideas is accompanied by increasing the alpha wave. The main goal of this study is to observe the relationship between the four characteristics of creativity (fluency, originality, refinement and flexibility) and the alpha wave variation, and we also observe the creative thinking method is able to improve the creation of students at the same time. The experimental results show the original play the most important role in the four characteristics of creativity. It means the students with relatively high originality will be measured more alpha wave in the creative thinking activity. On the contrary, if the students’ creative character lacks originality, then the alpha wave may not increase as expected. By the way, we also get the result a relatively high alpha wave is measured when the students try to use the creative thinking method for solving problems.

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Correspondence to Chin-Feng Lai .

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Chen, SY., Lai, CF., Hwang, RH., Yang, CS., Wang, MS. (2017). Inference of Learning Creative Characteristics by Analysis of EEG Signal. In: Huang, TC., Lau, R., Huang, YM., Spaniol, M., Yuen, CH. (eds) Emerging Technologies for Education. SETE 2017. Lecture Notes in Computer Science(), vol 10676. Springer, Cham. https://doi.org/10.1007/978-3-319-71084-6_49

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  • DOI: https://doi.org/10.1007/978-3-319-71084-6_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71083-9

  • Online ISBN: 978-3-319-71084-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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