Modelling Study on Learning Affects for Classroom Teaching/Learning Auto-Evaluation
Science Journal of Education
Volume 6, Issue 3, June 2018, Pages: 81-86
Received: Jun. 19, 2018;
Published: Jun. 20, 2018
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Minyu Pan, College of Information Science and Technology, Beijing Normal University, Beijing, China
Jing Wang, College of Information Science and Technology, Beijing Normal University, Beijing, China; Engineering Research Center of Virtual Reality and Applications, Ministry of Education, Beijing, China
Zuying Luo, College of Information Science and Technology, Beijing Normal University, Beijing, China; Engineering Research Center of Virtual Reality and Applications, Ministry of Education, Beijing, China
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In studies on classroom teaching auto-evaluation, we have achieved some remarkable results in Classroom Attendance Auto-management, learning attention & facial expression auto-analysis. For further utilizing learning affects to auto-evaluate classroom teaching/learning effects, we watch a large number of classroom videos. Then, based on the stimulus-response mechanism, we use learning facial expressions & attention to categorize students’ learning affects (SLA) and construct a SLA transfer model. At last, we simply describe how to use SLA analysis results to auto-evaluate the classroom teaching/learning effects. This work lays a theoretical foundation for the studies on learning facial expressions and learning affects for classroom teaching/learning auto-evaluation.
Learning Affect, Classroom Evaluation, Affect Modelling, Facial Expression Recognition
To cite this article
Modelling Study on Learning Affects for Classroom Teaching/Learning Auto-Evaluation, Science Journal of Education.
Vol. 6, No. 3,
2018, pp. 81-86.
Bloom etc. Educational Evaluation [M]. East China Normal University Press, 1987 edition.
Jihui Li. How to evaluate emotion, attitude and values [J]. Educational Science Research, 2006, 02:23-26.
Cai Min. A Study on the Evaluation of Elementary Student Affection in Mathematics Learning [J]. Education Science, 2010, 26(1): 26-30.
Kaifeng Liu and Xiaoguo Lv. The Conception of Mathematics Learning Emotion Evaluation Indicator System [J]. Journal of Higher Correspondence Education (Natural Sciences), 2009, 26(1): 26-30.
Huili Tang. Research on the Evaluation of Student’s Studying Emotion [D], Henan: Henan University, 2009.
Yi Shen and Yunhuo Cui. Class Observation: Towards professional listening and evaluation [M]. East China Normal University Press, 2008.
Chongsheng Zhang. Deep Learning: Principles and Application Practices [M]. Publishing House of Electronics Industry, 2016.
Chuangao Tang, Pengfei Xu, Zuying Luo, etc., Automatic Facial Expression Analysis of Students in Teaching Environment [C]. 10th Chinese Conference on Biometric Recognition (CCBR), LNCS 9482, 2015: 439-447.
Scotti S etc. Automatic quantitative evaluation of emotions in E-learning applications [C]. Engineering in Medicine and Biology Society, Annual International Conference of the IEEE, 2006: 1359-1362.
Krithika etc. Student Emotion Recognition System (SERS) for e-learning Improvement Based on Learner Concentration Metric [J]. Procedia Computer Science, 2016, 85: 767-776.