IEEE Access (Jan 2019)

A Hybrid Biological Data Analysis Approach for Students’ Learning Creative Characteristics Recognition

  • Shih-Yeh Chen,
  • Chin-Feng Lai,
  • Chi-Cheng Chang

DOI
https://doi.org/10.1109/ACCESS.2019.2940378
Journal volume & issue
Vol. 7
pp. 134411 – 134421

Abstract

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Regarding the effectiveness evaluation of students' creativity learning, most of the past studies have proposed teaching strategies to improve the creativity of students. For example, teachers use traditional questionnaires to evalute students' creativity learning effectiveness after implementing teaching strategies. However, most traditional questionnaires lack automated methods to provide immediate feedback to help teachers understand the current learning status of students instantly. Based on the above problem description, a hybrid biological data analysis approach is proposed that the teachers can analysis the students' learning status in the learning process through the wearable biological monitoring devices. Hybrid biological data such as the degree of course participation and creativity growth of the students is collected to be analyzed for recognizing students' learning creative characteristics. In the experiment results, we observed that the changes in brainwave values and heartbeats echoed the students' creativity status.

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