TY - JOUR
T1 - Facial micro-expression states as an indicator for conceptual change in students' understanding of air pressure and boiling points
AU - Chiu, Mei Hung
AU - Liaw, Hongming Leonard
AU - Yu, Yuh Ru
AU - Chou, Chin Cheng
N1 - Funding Information:
This project was supported by grants from the Taiwanese Ministry of Science and Technology (NSC 102?2511-S-003?006-MY3; MOST 104?2811-S-003?011 and MOST 103?2811-S-003?007; Post-Doc 102?2811-S-003?006 and Post-Doc 102?2811-S-003?007). The authors would like to express their appreciation for the funding of this project.
Funding Information:
This project was supported by grants from the Taiwanese Ministry of Science and Technology (NSC 102–2511-S-003–006-MY3; MOST 104–2811-S-003–011 and MOST 103–2811-S-003–007; Post-Doc 102–2811-S-003–006 and Post-Doc 102–2811-S-003– 007). The authors would like to express their appreciation for the funding of this project.
PY - 2019/1
Y1 - 2019/1
N2 - Utilizing facial recognition technology, the current study has attempted to predict the likelihood of student conceptual change with decision tree models based on the facial micro-expression states (FMES) students exhibited when they experience conceptual conflict. While conceptual change through conceptual conflicts in science education is a well-studied field, there is little research done on conceptual change through conceptual conflict in terms of students' facial expressions. As facial expressions are one of the most direct and immediate responses one can get during instruction and that facial expressions are often representations student's emotions, a link between students' FMES and learning was explored. Facial data was collected from 90 tenth graders. Only data from the 72 students who made incorrect predictions were analyzed in this study. The concept taught was the relationship between boiling point and air pressure. Through facial recognition software analysis and decision tree models, the current study found Surprised, Sad and Disgusted to be key FMES that could be used to predict student conceptual change in a conceptual conflict-based scenario.
AB - Utilizing facial recognition technology, the current study has attempted to predict the likelihood of student conceptual change with decision tree models based on the facial micro-expression states (FMES) students exhibited when they experience conceptual conflict. While conceptual change through conceptual conflicts in science education is a well-studied field, there is little research done on conceptual change through conceptual conflict in terms of students' facial expressions. As facial expressions are one of the most direct and immediate responses one can get during instruction and that facial expressions are often representations student's emotions, a link between students' FMES and learning was explored. Facial data was collected from 90 tenth graders. Only data from the 72 students who made incorrect predictions were analyzed in this study. The concept taught was the relationship between boiling point and air pressure. Through facial recognition software analysis and decision tree models, the current study found Surprised, Sad and Disgusted to be key FMES that could be used to predict student conceptual change in a conceptual conflict-based scenario.
UR - http://www.scopus.com/inward/record.url?scp=85034772449&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85034772449&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/facial-microexpression-states-indicator-conceptual-change-students-understanding-air-pressure-boilin
U2 - 10.1111/bjet.12597
DO - 10.1111/bjet.12597
M3 - Article
AN - SCOPUS:85034772449
VL - 50
SP - 469
EP - 480
JO - British Journal of Educational Technology
JF - British Journal of Educational Technology
SN - 0007-1013
IS - 1
ER -