In collaboration with Payame Noor University and Iran Educational Psychology Association

Document Type : Research

Authors

1 assistant professor in computer science- Department of educational technology- faculty of psychology and education- Allameh Tabataba'i University

2 Professor, Faculty of Psychology and Educational Sciences, Allameh Tabataba’i University

3 Associate Professor, Clinical Psychology, Allameh Tabataba’i University

4 Assistant Professor / Allameh Tabataba’i University

Abstract

This research focuses on designing an educational system architecture which is based on compound affective feedback and then measuring its impact on users’ learning and satisfaction. The research method is quasi-experimental which uses pre and post-test with control group to measure the effectiveness of the system on the users learning and satisfaction. The study population covers all MA educational technology students in the city of Tehran for academic year 2017-18. For this, using a convenience sampling method, 20 students are selected from MA educational technology students at Allameh Tabataba’I University; then, they are divided into two groups as control and experiment (each of 10). In this research, learning test (with reliability of 0.83) and E-Game-Flow questionnaire are utilized. For data analysis, descriptive (Mean and Standard Deviation) and Inferential statistics (one-variable analysis of covariance) are used. The results show that utilizing compound affective feedback in educational systems, positively influences the users' learning and satisfaction.

Keywords

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ایل‌بیگی، الناز؛ یزدچی، محمدرضا؛ مهنام، امین (1393). طراحی سیستم پیشرفته‌ای برای بازشناسی احساسات بر اساس سیگنال‌های مغزی و تصاویر چهره. مجله علمی سازمان نظام پزشکی جمهوری اسلامی ایران، دوره 32، شماره 1، بهار 40-27
فلاحتی، فرزاد؛ جوادیان نیک، مرضیه (1393). بررسی تأثیر نوع موسیقی بر سیگنال EEG. همایش ملی مهندسی برق، مخابرات و توسعه پایدار.
مروی، حسین؛ اسماعیلیان، زینب (1392). معرفی پایگاه داده فارسی جهت تشخیص احساس از روی گفتار، بیست و یکمین کنفرانس مهندسی برق ایران.
 
 
 
Ardakani, S., P. (2017). An Adaptive Game Design Model using the Fusion of Complementary Affective Signs, International Conference on Cognitive Science, 3-7 April. Tehran. Iran.
Atkinson, A. P., Dittrich, W. H., Gemmell, A. J., & Young, A. W. (2004). Emotion Perception from Dynamic and Static Body Expressions in Point-light and Full-light Displays. Perception-London, 33, pp. 717–746.
Bernhardt, D. (2010). Emotion inference from human body motion. PhD thesis, University of Cambridge, UK.
Fu, F., Su, R., & Yu, S. (2009). EGameFlow: A Scale to Measure Learners’ enjoyment of e-learmning games. Computer and Educations, 52, pp. 101-112.
Grinde, B. (2012). The biology of happiness. Berlin, Germany: Springer Science & Business Media.
Hehman, E., Flake, J.K., & Freeman, J.B. (2015). Static and Dynamic Facial Cues Differentially Affect the Consistency of Social Evaluations. Personality and Social Psychology Bulletin, 41(8), pp.1123-34.
Jang, E. H., Park, B. J., Park, M. S., Kim, S. H., & Sohn, J. H. (2015). Analysis of physiological signals for recognition of boredom, pain, and surprise emotions. Journal of physiological anthropology, 34(1), pp. 25.
Kapur, A., Kapur, A., Virji-Babul, N., Tzanetakis, G. (2005). Gesture-Based Affective Computing on Motion Capture Data. Affective Computing and Intelligent Interaction, 3784, pp. 1-12.
Kleisner, K., Chvatalova, V. & Flegr, J. (2014). Perceived Intelligence Is Associated with Measured Intelligence in Men but Not Women. PLOS One, 9(3), pp. 20.
Liu, Y., Sourina, O., & Nguyen, M. (2011). Real-time EEG-based Emotion Recognition and its Applications. Transactions on Computer Sceince XII, 6670, pp. 256-277.
Neel, R., Becker, D.V., Neuberg, S. L. & Kenrick, D. T. (2012). Who expressed what emotion? Men grab anger, women grab happiness. Journal of Experimental Social Psychology, 48, pp. 583–586.
Neiberg, D., Elenius, K., & Laskowski, K. (2006). Emotion Recognition in Spontaneous Language Processing. Ninth International Conference on Spoken Language, 17-21 September, 802-813, Pennsylvania, USA.
Or, J. (2008). Affective Computing: focus on emotion expression, synthesis and expression. Vienna, Austria: I-tech education and publishing.
Pedersen Kvaale, S. (2012). Emotion Recognition in EEG. MSc. Thesis, Computer Science Department, NUNT, Trondheim, Norway.
Saha, S., Datta, S., Konar, A., & Janartanan, R. (2014). A study on emotion recognition from body gesture using Kinect sensor. International Conference on Communication and Signal Processing, April 3-5, india.
Sayette, M., Cohn, J. F., Wertz, J. M., Perrott, M. A., & Parrott, D. J. (2001). A Psychometric Evaluation of the Facial Action Coding System for Assessing Spontaneois Experssion. Journal of Nonverbal Behaviour, 25(3). pp. 167-185.
Stickel, C., Ebner, M., Steinbach-Nordmann, S., Searle, G., & Holzinger, A. (2010). Emotion Detection: Application of the Valence Arousal Space for Rapid Biological Usability Testing to enhance Universal Access. HCI, 5, pp. 615–624.
Stolarski, Ł. (2016). Pitch Patterns in Vocal Expression of “Happiness” and “Sadness” in the Reading Aloud of Prose on the Basis of Selected Audiobooks. Research in Language, 13(2), pp. 141-162.
Tian, Y., Kanade, T., & Cohn, J. (2011). Facial Experssion Recognition. Springer-verlag, London.
Yeh P., Geangu E., & Reid, V. (2016). Coherent emotional perception from body expressions and the voice, Neuropsychologic, 1, pp. 99-108.
Zhang, L. & Tjondronegorom D. (2011). Facial Experssion Recognition Using Facial Movment Features. IEEE Transactions on Affective Computing, 2(4), pp. 219-229.