Measuring emotions in education using wearable devices: A systematic review

被引:29
作者
Ba, Shen [1 ]
Hu, Xiao [1 ,2 ]
机构
[1] Univ Hong Kong, Fac Educ, Hong Kong, Peoples R China
[2] Univ Hong Kong, Room 209, Runme Shaw Bldg, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Teaching; learning strategies; Data science applications in education; Evaluation methodologies; Distributed learning environments; DIFFERENT MULTIMEDIA MATERIALS; COGNITIVE LOAD; ELECTRODERMAL ACTIVITY; ACHIEVEMENT EMOTIONS; SERIOUS GAME; INTELLIGENT; STRESS; MODEL; RECOGNITION; AROUSAL;
D O I
10.1016/j.compedu.2023.104797
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Wearable devices that detect real-time and fine-grained physiological signals offer potentials for understanding the intricate mechanisms of emotions in education. However, due to the diversities of wearable devices, physiological signals, educational emotions, and educational contexts, there is lack of consensus on the affordance and constraints of wearable devices for measuring emotions in education. The present study conducted a systematic literature review and examined 50 peer -reviewed journal articles and influential proceedings published over the last 15 years (January 2008 to December 2022). Five research questions were addressed concerning research back-grounds, theoretical frameworks, methodologies, remaining challenges, and ethical consider-ations. Findings demonstrated that while most studies focused on university students in controlled environments, recent advances in wearable devices have enabled emotion measure-ments of younger learners in natural settings. Research interests have developed towards un-derstanding the theoretical connections between emotion and cognition leveraging wearable devices. Electrodermal activity and heart rate were the most frequently measured signals whereas "engagement", "positive", and "anxiety" were the most studied emotions. Machine learning and inferential statistics were often adopted to examine associations between physiological signals and educational emotions. Moreover, we identified a need for updated ethical guidelines in advanced data collection using wearable devices. This review can not only inform wearable de-vice usages in educational practices but also shed light on future research.
引用
收藏
页数:20
相关论文
共 147 条
[1]   Investigating teacher stress when using technology [J].
Al-Fudail, Mohammed ;
Mellar, Harvey .
COMPUTERS & EDUCATION, 2008, 51 (03) :1103-1110
[2]   FRUSTRATION THEORY - MANY YEARS LATER [J].
AMSEL, A .
PSYCHOLOGICAL BULLETIN, 1992, 112 (03) :396-399
[3]  
[Anonymous], 2007, EMOTION ED
[4]  
[Anonymous], 1979, SOCIAL PSYCHOL INTER
[5]   Biosensor Real-Time Affective Analytics in Virtual and Mixed Reality Medical Education Serious Games: Cohort Study [J].
Antoniou, Panagiotis E. ;
Arfaras, George ;
Pandria, Niki ;
Athanasiou, Alkinoos ;
Ntakakis, George ;
Babatsikos, Emmanouil ;
Nigdelis, Vasilis ;
Bamidis, Panagiotis .
JMIR SERIOUS GAMES, 2020, 8 (03)
[6]   EEG-based measurement system for monitoring student engagement in learning 4.0 [J].
Apicella, Andrea ;
Arpaia, Pasquale ;
Frosolone, Mirco ;
Improta, Giovanni ;
Moccaldi, Nicola ;
Pollastro, Andrea .
SCIENTIFIC REPORTS, 2022, 12 (01)
[7]   Emotion Recognition from Multimodal Physiological Signals for Emotion Aware Healthcare Systems [J].
Ayata, Deger ;
Yaslan, Yusuf ;
Kamasak, Mustafa E. .
JOURNAL OF MEDICAL AND BIOLOGICAL ENGINEERING, 2020, 40 (02) :149-157
[8]   Supporting adolescents' digital well-being in the post pandemic era: Preliminary results from a multimodal learning analytics approach [J].
Ba, Shen ;
Hu, Xiao ;
Kong, Runzhi ;
Law, Nancy .
2022 INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT 2022), 2022, :177-179
[9]   Understanding Emotion in Adolescents: A Review of Emotional Frequency, Intensity, Instability, and Clarity [J].
Bailen, Natasha H. ;
Green, Lauren M. ;
Thompson, Renee J. .
EMOTION REVIEW, 2019, 11 (01) :63-73
[10]  
Barrett LF, 2017, SOC COGN AFFECT NEUR, V12, P1, DOI [10.1093/scan/nsx060, 10.1093/scan/nsw154]