Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective

被引:30
作者
Charland, Patrick [1 ]
Leger, Pierre-Majorique [2 ,3 ]
Senecal, Sylvain [3 ,4 ]
Courtemanche, Francois [2 ,3 ]
Mercier, Julien [5 ]
Skelling, Yannick [1 ]
Labonte-Lemoyne, Elise [2 ,3 ]
机构
[1] Univ Quebec Montreal, Dept Didact, Montreal, PQ, Canada
[2] HEC Montreal, Dept IT, Montreal, PQ, Canada
[3] HEC Montreal, Tech3Lab, Montreal, PQ, Canada
[4] HEC Montreal, Dept Mkt, Montreal, PQ, Canada
[5] Univ Quebec Montreal, Dept Specialized Educ, Montreal, PQ, Canada
来源
JOVE-JOURNAL OF VISUALIZED EXPERIMENTS | 2015年 / 101期
基金
加拿大自然科学与工程研究理事会;
关键词
Behavior; Issue; 101; Measurement of engagement; learning; neurophysiology; electroencephalography; signal synchronization; electrodermal activity; automatic facial emotion recognition; emotional valence; arousal; BIOCYBERNETIC SYSTEM; INDEXES; IMPACT;
D O I
10.3791/52627
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
In a recent theoretical synthesis on the concept of engagement, Fredricks, Blumenfeld and Paris1 defined engagement by its multiple dimensions: behavioral, emotional and cognitive. They observed that individual types of engagement had not been studied in conjunction, and little information was available about interactions or synergy between the dimensions; consequently, more studies would contribute to creating finely tuned teaching interventions. Benefiting from the recent technological advances in neurosciences, this paper presents a recently developed methodology to gather and synchronize data on multidimensional engagement during learning tasks. The technique involves the collection of (a) electroencephalography, (b) electrodermal, (c) eye-tracking, and (d) facial emotion recognition data on four different computers. This led to synchronization issues for data collected from multiple sources. Post synchronization in specialized integration software gives researchers a better understanding of the dynamics between the multiple dimensions of engagement. For curriculum developers, these data could provide informed guidelines for achieving better instruction/learning efficiency. This technique also opens up possibilities in the field of brain-computer interactions, where adaptive learning or assessment environments could be developed.
引用
收藏
页码:1 / 8
页数:8
相关论文
共 26 条
  • [1] Allaire-Duquette G., 2014, European Journal of Physics Education, V5, P31, DOI [DOI 10.20308/ejpe.93516, 10.20308/ejpe.v5i2.66, DOI 10.20308/EJPE.V5I2.66]
  • [2] Boucsein W, 2012, ELECTRODERMAL ACTIVITY, SECOND EDITION, P1, DOI 10.1007/978-1-4614-1126-0
  • [3] MEASURING EMOTION - THE SELF-ASSESSMENT MANNEQUIN AND THE SEMANTIC DIFFERENTIAL
    BRADLEY, MM
    LANG, PJ
    [J]. JOURNAL OF BEHAVIOR THERAPY AND EXPERIMENTAL PSYCHIATRY, 1994, 25 (01) : 49 - 59
  • [4] Cacioppo JT, 2007, HANDBOOK OF PSYCHOPHYSIOLOGY, 3RD EDITION, P1, DOI 10.2277/ 0521844711
  • [5] Chaouachi M., 2010, P 23 INT FLOR ART IN, P355
  • [6] Charland P., 2014, 4 SCI INT S ASS RES
  • [7] Clark RC, 2011, E-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning, 3rd Edition, P1, DOI 10.1002/9781118255971
  • [8] Courtemanche F., 2014, J ASSOC INF SYST, V15
  • [9] Courtemanche F., 2014, THESIS U MONTREAL MO
  • [10] FELT, FALSE, AND MISERABLE SMILES
    EKMAN, P
    FRIESEN, WV
    [J]. JOURNAL OF NONVERBAL BEHAVIOR, 1982, 6 (04) : 238 - 252