A hybrid biological data analysis approach for students' learning creative characteristics recognition

Shih Yeh Chen, Chin Feng Lai, Chi Cheng Chang

研究成果: 雜誌貢獻文章

摘要

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.

原文英語
文章編號8831391
頁(從 - 到)134411-134421
頁數11
期刊IEEE Access
7
DOIs
出版狀態已發佈 - 2019 一月 1

ASJC Scopus subject areas

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

指紋 深入研究「A hybrid biological data analysis approach for students' learning creative characteristics recognition」主題。共同形成了獨特的指紋。

  • 引用此