Investigation of educational processes with affective computing methods - Publikacja - MOST Wiedzy

Wyszukiwarka

Investigation of educational processes with affective computing methods

Abstrakt

This paper concerns the monitoring of educational processes with the use of new technologies for the recognition of human emotions. This paper summarizes results from three experiments, aimed at the validation of applying emotion recognition to e-learning. An analysis of the experiments’ executions provides an evaluation of the emotion elicitation methods used to monitor learners. The comparison of affect recognition algorithms was based on the criteria of availability, accuracy, robustness to disturbance, and interference with the e-learning process. The lessons learned in these experiments might be of interest to teachers and e-learning tutors, as well as to those researchers who want to use affective computing methods in monitoring educational processes.

Cytowania

  • 1

    CrossRef

  • 0

    Web of Science

  • 0

    Scopus

Cytuj jako

Pełna treść

pobierz publikację
pobrano 4 razy
Wersja publikacji
Accepted albo Published Version
Licencja
Copyright (Autorzy i E-mentor)

Słowa kluczowe

Informacje szczegółowe

Kategoria:
Publikacja w czasopiśmie
Typ:
artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Opublikowano w:
e-mentor strony 15 - 24,
ISSN: 1731-6758
Język:
angielski
Rok wydania:
2017
Opis bibliograficzny:
Landowska A., Brodny G.: Investigation of educational processes with affective computing methods// e-mentor. -., nr. 3(70) (2017), s.15-24
DOI:
Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.15219/em70.1304
Bibliografia: test
  1. Ang, J., Dhillon, R., Krupski, A., Shriberg, E., & Stolcke, A. (2002). Prosody-based automatic detection of annoy- ance and frustration in human-computer dialog. Proceed- ings of the 7th International Conference on Spoken Language Processing (ICSLP 2002), 2037-2040.
  2. Bailenson, J.N., Pontikakis, E.D., Mauss, I.B., Gross, J.J., Jabon, M.E., Hutcherson, C.A.C, & John, O. (2008). Real- time classification of evoked emotions using facial feature tracking and physiological responses. International Journal of Human-Computer Studies, 66(5), 303-317. http://dx.doi. org/10.1016/j.ijhcs.2007.10.011 otwiera się w nowej karcie
  3. Baker, R.S.J. d. (2007). Modeling and understanding students' off-task behavior in intelligent tutoring systems. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 1059. Ben Ammar, M., Neji, M., Alimi, A.M., & Gouardères, G. (2010). The affective tutoring system. Expert Systems with Applications, 37(4), 3013-3023. http://dx.doi.org/10.1016/ j.eswa.2009.09.031 otwiera się w nowej karcie
  4. Bessière, K., Newhagen, J.E., Robinson, J.P., & Shnei- derman, B. (2006). A model for computer frustration: The role of instrumental and dispositional factors on incident, session, and post-session frustration and mood. Computers in Human Behavior, 22(6), 941-961. otwiera się w nowej karcie
  5. Binali, H., Wu, C., & Potdar, V. (2009), A new signifi- cant area: Emotion detection in e-learning using opinion mining techniques. 3rd IEEE International Conference on Digital Ecosystems and Technologies, 259-264. http://dx.doi. org/10.1109/DEST.2009.5276726 otwiera się w nowej karcie
  6. Binali, H., Wu, C., & Potdar, V. (2010). Computational approaches for emotion detection in text. 4th IEEE Interna- tional Conference on Digital Ecosystems and Technologies -IEEE DEST, 172-177. otwiera się w nowej karcie
  7. Boehner, K., Depaula, R., Dourish, P., & Sengers, P. (2007). How emotion is made and measured. International Journal of Human-Computer Studies, 65(4), 275-291. http:// dx.doi.org/10.1016/j.ijhcs.2006.11.016 otwiera się w nowej karcie
  8. Elliott, C., Rickel, J., & Lester, J.C. (1999). Lifelike peda- gogical agents and affective computing: An exploratory synthesis. Lecture notes on artificial intelligence. Artificial Intelligence Today, 1600, 195-211. Goleman, D. (2006). Emotional intelligence. USA: Bantam. Gunes, H., & Schuller, B. (2013). Categorical and dimensional affect analysis in continuous input: Cur- rent trends and future directions. Image and Vision Computing, 31(2), 120-136. http://dx.doi.org/10.1016/ j.imavis.2012.06.016 otwiera się w nowej karcie
  9. Hone, K. (2006). Empathic agents to reduce user frustration: The effects of varying agent characteristics. Interacting with Computers 18(2), 227-245. http://dx.doi. org/10.1016/j.intcom.2005.05.003 otwiera się w nowej karcie
  10. Hudlicka, E. (2003). To feel or not to feel: The role of affect in human-computer interaction. The International Journal of Human-Computer Studies, 59(1-2), 1-32. http:// dx.doi.org/10.1016/S1071-5819(03)00047-8 otwiera się w nowej karcie
  11. Kapoor, A., Mota, S., & Picard, R.W. (2001). Towards a learning companion that recognizes affect. Association for Advancement of Artificial Intelligence Fall Symposium, 543, 2-4. otwiera się w nowej karcie
  12. Kołakowska, A. (2013). A review of emotion recogni- tion methods based on keystroke dynamics and mouse movements. 6th International Conference on Human System Interactions. http://dx.doi.org/10.1109/HSI.2013.6577879 otwiera się w nowej karcie
  13. Landowska, A. (2013). Affective computing and affec- tive learning -methods, tools and prospects. EduAkcja. Magazyn edukacji elektronicznej, 1(5), 16-31. Landowska, A. (2015a). Emotion monitor -Concept, construction and lessons learned. Proceedings of the 2015 otwiera się w nowej karcie
  14. Federated Conference on Computer Science and Information Systems, FedCSIS 2015, 75-80. otwiera się w nowej karcie
  15. Landowska, A. (2015b). Towards emotion acquisition in IT usability evaluation context. Proceedings of the Muli- timedia, Interaction, Design and Innnovation on ZZZ -MIDI, 1-9. otwiera się w nowej karcie
  16. Landowska, A. (2016). How to design affect-aware edu- cational systems-the AFFINT process approach. Proceedings on the European Conference of e-Learning 2016. Landowska, A., & Brodny, G. (2017). Postrzeganie inwazyjności automatycznego rozpoznawania emocji w kontekście edukacyjnym. EduAkcja. Magazyn edukacji elektronicznej, 1(13), 26-41.
  17. Landowska, A., Brodny, G., & Wróbel, M.R. (2017). otwiera się w nowej karcie
  18. Limitations of emotion recognition from facial expres- sions in e-learning context. 9th International Conference on Computer Supported Education, 383-389. http://dx.doi. org/10.5220/0006357903830389 otwiera się w nowej karcie
  19. Landowska, A., & Miler, J. (2016). Limitations of emo- tion recognition in software user experience evaluation context. Federated Conference on Computer Science and Information Systems, 1631-1640. otwiera się w nowej karcie
  20. Li, J., & Ren, F. (2008). Emotion recognition from blog articles. International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE. otwiera się w nowej karcie
  21. Ling, H. S., Bali, R., & Salam R.A. (2006). Emotion detec- tion using keywords spotting and semantic network. Paper presented at the International Conference on Computing and Informatics ICOCI. otwiera się w nowej karcie
  22. Maria, K.A., & Zitar, R.A. (2007). Emotional agents: A modeling and an application. Information and Software Technology, 49(7), 695-716, http://dx.doi.org/10.1016/ j.infsof.2006.08.002 otwiera się w nowej karcie
  23. Mehrabian, A. (1996). Pleasure-arousal. Dominance: A general framework for describing and measuring in- dividual differences in temperament. Current Psychology, 14(4), 261-292. otwiera się w nowej karcie
  24. Neviarouskaya, A., Prendinger, H., & Ishizuka, M. (2009). otwiera się w nowej karcie
  25. Compositionality principle in recognition of fine-grained emotions from text. International Association for Advance- ment of Artificial Intelligence Conference on Web and Social Media, 278-281. otwiera się w nowej karcie
  26. Paiva, A., Dias, J., Sobral, D., & Woods, S. (2004). Build- ing empathic lifelike characters: the proximity factor. In- ternational Conference on Autonomous Agents and Multiagent Systems, 4.
  27. Picard, R.W. (2003). Affective computing: challenges. otwiera się w nowej karcie
  28. The International Journal of Human-Computer Studies, 59(1-2), 55-64. http://dx.doi.org/10.1016/S1071-5819(03)00052-1 otwiera się w nowej karcie
  29. Picard, R.W., & Ahn, H. (2006). Affective cognitive learn- ing and decision making: The role of emotions. Lecture Notes in Computer Science book series, 3784, 866-873.
  30. Picard, R.W., & Daily, S. (2005). Evaluating affective interactions: Alternatives to asking what users feel. Pro- ceedings CHI'05 Workshop on Evaluating Affective Interfaces: Innovative Approaches.
  31. Picard, R.W., & Klein, J. (2002). Computers that recog- nise and respond to user emotion: theoretical and practical implications. Interacting with Computers, 14(2), 141-169. http://dx.doi.org/10.1016/S0953-5438(01)00055-8 otwiera się w nowej karcie
  32. Scheirer, J., Fernandez, R., Klein, J., & Picard, R.W. (2002). Frustrating the user on purpose: a step toward building an affective computer. Interacting with Comput- ers, 14(2), 93-118. http://dx.doi.org/10.1016/S0953- 5438(01)00059-5 otwiera się w nowej karcie
  33. Scherer, K.R., & Ekman, P. (1984). Approaches to emotion. Hillsdale, NJ: L. Erlbaum Associates. Sheng, Z., Zhu-ying, L., & Wan-xin, D. (2010). The model of E-learning based on affective computing. 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE), 3, 269-272.
  34. Strapparava, C., & Valitutti, A. (2004). WordNet-Affect: an affective extension of WordNet. 4th International Confer- ence on Language Resources and Evaluation, 1083-1086. Wioleta, S. (2013). Using physiological signals for emo- tion recognition. The 6th International Conference on Human System Interaction, 556-561.
  35. Woolf, B., Burleson, W., & Arroyo, I. (2009). Affect-aware tutors: recognising and responding to student affect. In- ternational Journal of Learning Technology, 4(3/4), 129-164. http://dx.doi.org/10.1504/IJLT.2009.028804 otwiera się w nowej karcie
  36. Yik, M.S. M., Russell, J.A., & Barrett, L.F. (1999). Structure of self-reported current affect: Integration and beyond. Journal of Personality and Social Psychology, 77(3), 600-619. http://dx.doi.org/10.1037/0022-3514.77.3.600 otwiera się w nowej karcie
  37. Zeng, Z., Pantic, M., Roisman, G.I., & Huang, T. S. (2007). otwiera się w nowej karcie
  38. A survey of affect recognition methods. Proceedings of the 9th International Conference on Multimodal Interfaces. Paper presented at ICMI 2007 in Nagoya, Japan, November 12-15 (pp. 126-133). http://dx.doi.org/10.1145/1322192.1322216 otwiera się w nowej karcie
Weryfikacja:
Politechnika Gdańska

wyświetlono 41 razy

Publikacje, które mogą cię zainteresować

Meta Tagi