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Emotion-Aware Educational System: The Lecturers and Students Perspectives in Malaysia

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Book cover Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication (IMCOM) 2019 (IMCOM 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 935))

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Abstract

Emotion-aware educational system may feature the online education system in the near future. However, the current studies discussed more the technical implementation and how important to consider emotion in education. Receiving an input from lecturers and students may enrich the knowledge of the developers of emotion aware systems. This paper surveyed lecturers and students from one Malaysian University, and the findings showed students and lecturers have high interest in consideration of emotions in education process. However they raised many challenges such as to what extent lecturers should consider emotions when engaged with students? Do students provide enough input particularly in blended learning system where students prefer meeting lecturers face-to-face? It has been noticed that lecturers were motivating students to engage online and students show lack of self-motivation to engage independently. Eventually, lecturers were concerned about what types of emotion extraction/recognition tools should be considered? For instance, facial recognition and sound tone analysis require student to have visual/audio interaction with the system, as well as they are expensive and complicated to be implemented. Lectures proposed that statistical procedures and artificial intelligence techniques should be used to understand better the emotional patterns. Lecturers consider that utilizing the emotion analysis for mouse movement and keystroke while student are doing quizzes, assignments, tests, and exams will provide more findings than analyzing only textual communication with lecturers.

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Change history

  • 06 August 2019

    The original version of this chapter was published without a reference to an earlier chapter. This has now been rectified and the reference has been added.

References

  1. Aljohani, N.R., Daud, A., Abbasi, R.A., Alowibdi, J.S., Basheri, M., Aslam, M.A.: An integrated framework for course adapted student learning analytics dashboard. Comput. Hum. Behav. 92, 679–690 (2018)

    Article  Google Scholar 

  2. Rodriguez, P., Ortigosa, A., Carro, R.M.: Extracting emotions from texts in e-learning environments. Presented at the 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems (2012)

    Google Scholar 

  3. Gil-Olarte Márquez, P., Palomera Martín, R., Brackett, M.: Relating emotional intelligence to social competence and academic achievement in high school students. Psicothema 18, 118–123 (2006)

    Google Scholar 

  4. Nelson, R., Benner, G., Lane, K., Smith, B.: Academic achievement of K-12 students with emotional and behavioral disorders. Except. Child. 71, 59–73 (2004)

    Article  Google Scholar 

  5. Parker, J., Creque, R., Barnhart, D., Harris, J.I., Majeski, S.A., Wood, L.: Academic achievement in high school: does emotional intelligence matter? Pers. Individ. Differ. 37(7), 1321–1330 (2004)

    Article  Google Scholar 

  6. Reyes, M.R., Brackett, M.A., Rivers, S.E., White, M., Salovey, P.: Classroom emotional climate, student engagement, and academic achievement. J. Educ. Psychol. 104(3), 700–712 (2012)

    Article  Google Scholar 

  7. Feidakis, M., Daradoumis, T., Caballé, S., Conesa, J.: Measuring the impact of emotion awareness on e-learning situations. Presented at the 2013 Seventh International Conference on Complex, Intelligent, and Software Intensive Systems (2013)

    Google Scholar 

  8. Loia, V., Senatore, S.: A Fuzzy-oriented sentic analysis to capture the human emotion in Web-based content. Knowl. Based Syst. 58, 75–85 (2014)

    Article  Google Scholar 

  9. Pekrun, R., Goetz, T., Frenzel, A.C., Barchfeld, P., Perry, R.P.: Measuring emotions in students’ learning and performance: the Achievement Emotions Questionnaire (AEQ). Contemp. Educ. Psychol. 36, 36–48 (2011)

    Article  Google Scholar 

  10. Arguedas, M., Daradoumis, T., Xhafa, F.: Analyzing how emotion awareness influences students’ motivation, engagement, self-regulation and learning outcome. Educ. Technol. Soc. 19(2), 87–103 (2016)

    Google Scholar 

  11. Feidakis, M., Caballé, S., Daradoumis, T., Gañán, D., Conesa, J.: Providing emotion awareness and affective feedback to virtualized collaborative learning scenarios. Int. J. Contin. Eng. Educ. Life-Long Learn. (IJCEELL) 24(2), 141–167 (2014)

    Article  Google Scholar 

  12. Heylen, D., Nijholt, A., op den Akker, R.: Affect in tutoring dialogues. Appl. Artif. Intell. 19(3–4), 287–311 (2005)

    Article  Google Scholar 

  13. Davis, H.A., DiStefano, C., Schutz, P.A.: Identifying patterns of appraising tests in first-year college students: implications for anxiety and emotion regulation during test taking. J. Educ. Psychol. 100(4), 942–960 (2008)

    Article  Google Scholar 

  14. Bahreini, K., Nadolski, R., Westera, W.: Toward multimodal emotion recognition in e-learning environments. Interact. Learn. Environ. 24(3), 590–605 (2016)

    Article  Google Scholar 

  15. Colomo-Palacios, R., Casado-Lumbreras, C., Soto-Acosta, P., García-Crespo, A.: Using the affect grid to measure emotions in software requirements engineering. J. Univers. Comput. Sci. 17(9), 1281–1298 (2011)

    Google Scholar 

  16. Kim, C., Park, S.W., Cozart, J.: Affective and motivational factors of learning in online mathematics courses. Br. J. Educ. Technol. 45, 171–185 (2014)

    Article  Google Scholar 

  17. Arguedas, M., Daradoumis, T., Xhafa, F.: Analyzing the effects of emotion management on time and selfmanagement in computer-based learning. Comput. Hum. Behav. 63, 517–529 (2016)

    Article  Google Scholar 

  18. Feidakis, M.: A review of emotion-aware systems for e-learning in virtual environments. In: Formative Assessment, Learning Data Analytics and Gamification. Elsevier (2016)

    Google Scholar 

  19. Feidakis, M., Daradoumis, T., Caballé, S.: Emotion measurement in intelligent tutoring systems: what, when and how to measure. Presented at the 2011 Third International Conference on Intelligent Networking and Collaborative Systems (2011)

    Google Scholar 

  20. Gil, R., Virgili-Gomá, J., García, R., Mason, C.: Emotions ontology for collaborative modelling and learning of emotional responses. Comput. Hum. Behav. 51, 610–617 (2015)

    Article  Google Scholar 

  21. Arguedas, M., Xhafa, F., Daradoumis, T., Caballe, S.: An ontology about emotion awareness and affective feedback in elearning. Presented at the 2015 International Conference on Intelligent Networking and Collaborative Systems (2015)

    Google Scholar 

  22. Arguedas, M., Daradoumis, T., Xhafa, F.: Towards an emotion labeling model to detect emotions in educational discourse. Presented at the 8th International Conference on Complex, Intelligent and Software Intensive Systems (CISIS-2014), Los Alamitos, CA (2014)

    Google Scholar 

  23. Lang, P.J.: A bio-informational theory of emotional imagery. Psychophysiology 16, 495–512 (1979)

    Article  Google Scholar 

  24. Hsieh, H.-F., Shannon, S.E.: Three approaches to qualitative content analysis. Qual. Health Res. 15(9), 1277–1289 (2005)

    Article  Google Scholar 

  25. Vieira, C., Parsons, P., Byrd, V.: Visual learning analytics of educational data: a systematic literature review and research agenda. Comput. Educ. 122, 119–135 (2018)

    Article  Google Scholar 

  26. Che-Cheng, L., Chiung-Hui, C.: Correlation between course tracking variables and academic performance in blended online courses. Presented at the IEEE 13th International Conference on Advanced Learning Technologies (ICALT), Hong Kong (2013)

    Google Scholar 

  27. Roberge, D., Rojas, A., Baker, R.: Does the length of time off-task matter? Presented at the 2nd International Conference on Learning Analytics and Knowledge, Vancouver, BC, Canada (2012)

    Google Scholar 

  28. Laur, E.J.M., Baron, J.D., Devireddy, M., Sundararaju, V., Jayaprakash, S.M.: Mining academic data to improve college student retention: an open source perspective. Presented at the 2nd International Conference on Learning Analytics and Knowledge, Vancouver, BC, Canada (2012)

    Google Scholar 

  29. Pistilli, M.D., Arnold, K.E.: In practice: purdue signals: mining real-time academic data to enhance student success. About Campus 15(3), 22–24 (2010)

    Article  Google Scholar 

  30. Romero, C., López, M.-I., Luna, J.-M., Ventura, S.: Predicting students’ final performance from participation in on-line discussion forums. Comput. Educ. 60, 458–472 (2013)

    Article  Google Scholar 

  31. Bakharia, A., Dawson, S.: SNAPP: a bird’s-eye view of temporal participant interaction. Presented at the 1st International Conference on Learning Analytics and Knowledge, Banff, Alberta, Canada (2011)

    Google Scholar 

  32. Ferguson, R., Shum, S.B.: Social learning analytics: five approaches. Presented at the 2nd International Conference on Learning Analytics and Knowledge, Vancouver, BC, Canada (2012)

    Google Scholar 

  33. Shum, S.B., Ferguson, R.: Social learning analytics. J. Educ. Technol. Soc. 15(3), 3–26 (2012)

    Google Scholar 

  34. Gómez Aguilar, D.A., García-Peñalvo, F.J., Therón, R.: Tap into visual analysis of the customization of grouping of activities in eLearning. Presented at the 1st International Conference on Technological Ecosystem for Enhancing Multiculturality, Salamanca, Spain (2013)

    Google Scholar 

  35. Rosen, D., Miagkikh, V., Suthers, D.: Social and semantic network analysis of chat logs. Presented at the 1st International Conference on Learning Analytics and Knowledge, Banff, Alberta, Canada (2011)

    Google Scholar 

  36. Softic, S., Taraghi, B., Ebner, M., Vocht, L., Mannens, E., Walle, R.: Monitoring learning activities in PLE using semantic modelling of learner behaviour. Hum. Factors Comput. Inform. 7946, 74–90 (2013)

    Article  Google Scholar 

  37. Shikder, R., Rahaman, S., Afroze, F., Al Islam, A.B.M.: Keystroke/mouse usage based emotion detection and user identification. Presented at the 2017 International Conference on Networking, Systems and Security (NSysS), Dhaka, Bangladesh (2017)

    Google Scholar 

  38. Alharbi, L., Grasso, F., Jimmieson, P.: An experiment with an off-the-shelf tool to identify emotions in students’ self-reported accounts. In: Symposium on Emotion Modelling and Detection in Social Media and Online Interaction, pp. 16–21. AISB, Liverpool (2018)

    Google Scholar 

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Author information

Authors and Affiliations

  1. University of Kula Lumpur (UniKL), Kuala Lumpur, Malaysia

    Rasheed M. Nassr, Abdulaziz Hadi Saleh, Hassan Dao & Md. Nazmus Saadat

Authors
  1. Rasheed M. Nassr
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  2. Abdulaziz Hadi Saleh
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  3. Hassan Dao
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  4. Md. Nazmus Saadat
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Corresponding author

Correspondence to Rasheed M. Nassr .

Editor information

Editors and Affiliations

  1. Intelligent Systems Research Institute, Sungkyunkwan University, Suwon, Korea (Republic of)

    Sukhan Lee

  2. Software Engineering, Universiti Kuala Lumpur, Kuala Lumpur, Malaysia

    Roslan Ismail

  3. College of Software, Sungkyunkwan University, Suwon, Korea (Republic of)

    Hyunseung Choo

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Nassr, R.M., Saleh, A.H., Dao, H., Saadat, M.N. (2019). Emotion-Aware Educational System: The Lecturers and Students Perspectives in Malaysia. In: Lee, S., Ismail, R., Choo, H. (eds) Proceedings of the 13th International Conference on Ubiquitous Information Management and Communication (IMCOM) 2019. IMCOM 2019. Advances in Intelligent Systems and Computing, vol 935. Springer, Cham. https://doi.org/10.1007/978-3-030-19063-7_49

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