Inference of learning creative characteristics by analysis of EEG signal

Shih Yeh Chen, Chin Feng Lai, Ren Hung Hwang, Chu Sing Yang, Ming Shi Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationEmerging Technologies for Education - 2nd International Symposium, SETE 2017, Held in Conjunction with ICWL 2017, Revised Selected Papers
EditorsTien-Chi Huang, Rynson Lau, Yueh-Min Huang, Marc Spaniol, Chun-Hung Yuen
PublisherSpringer Verlag
Pages425-432
Number of pages8
ISBN (Print)9783319710839
DOIs
Publication statusPublished - 2017 Jan 1
Event2nd International Symposium on Emerging Technologies for Education, SETE 2017, held in Conjunction with the 16th International Conference on Web-based learning, ICWL 2017 - Cape Town, South Africa
Duration: 2017 Sep 202017 Sep 22

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10676 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Symposium on Emerging Technologies for Education, SETE 2017, held in Conjunction with the 16th International Conference on Web-based learning, ICWL 2017
CountrySouth Africa
CityCape Town
Period17-09-2017-09-22

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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