Challenges in the Development of Affective Collaborative Learning Environment with Artificial Peers

[1] I. Magnisalis, S. Demetriadis, and A. Karakostas, “Adaptive and Intelligent Systems for Collaborative Learning Support: A Review of the Field,” IEEE Transactions on Learning Technologies, vol. 4, no. 1, pp. 5–20, 2011. https://doi.org/10.1109/TLT.2011.210.1109/TLT.2011.2Search in Google Scholar

[2] Z. Cai, A. J. Hampton, A. C. Graesser, X. Hu, J. L. Cockroft, D. W. Shaffer, and M. C. Dorneich, “Roles of Talking Agents in Online Collaborative Learning Environments,” Design Recommendations for Intelligent Tutoring Systems: vol. 6 - Team Tutoring, pp. 169–177, 2018.Search in Google Scholar

[3] R. A. Sottilare, A. C. Graesser, X. Hu, and A. M. Sinatra, “Introduction to Team Tutoring & GIFT,” Design Recommendations for Intelligent Tutoring Systems: Volume 6 - Team Tutoring, pp. 1–15, 2018.Search in Google Scholar

[4] R. W. Picard, “Affective Computing,” Cambridge, Mass,: MIT Press, 1997. https://doi.org/10.1007/BF0123802810.1007/BF01238028Search in Google Scholar

[5] P. Sancho, R. Fuentes-Fernandez, and B. Fernandez-Manjon, “NUCLEO: Adaptive Computer Supported Collaborative Learning in a Role Game Based Scenario,” Proceedings of the 8th IEEE International Conference on Advanced Learning Technologies, pp. 671–675, 2008. https://doi.org/10.1109/ICALT.2008.14710.1109/ICALT.2008.147Search in Google Scholar

[6] A. S. Carlin, S. K. B. Perry, and A. G. Ostrander, “Dynamic Task Selection for Team Task Training Using Wearable Sensors and Multi-Agent Planning Models,” Design Recommendations for Intelligent Tutoring Systems: Volume 6 - Team Tutoring, pp. 63–71, 2018.Search in Google Scholar

[7] P. Näykki, “Affective and effective collaborative learning: process-oriented design studies in a teacher education context,” University of Oulu, Finland, 2014.10.1016/j.ijer.2014.07.001Search in Google Scholar

[8] M. Nummenmaa, “Emotions in a Web-based Learning Environment,” University of Turku, Finland, 2007.Search in Google Scholar

[9] L. Linnenbrink–Garcia and R. Pekrun, “Students’ emotions and academic engagement: Introduction to the special issue,” Contemporary Educational Psychology, vol. 36, no. 1, pp. 1–3, 2011. https://doi.org/10.1016/j.cedpsych.2010.11.00410.1016/j.cedpsych.2010.11.004Search in Google Scholar

[10] K. Selvarajah and D. Richards, “The use of emotions to create believable agents in a virtual environment,” Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, ACM Press, New York, pp. 13–20, 2005. https://doi.org/10.1145/1082473.108247610.1145/1082473.1082476Search in Google Scholar

[11] S.G. Barsade, “The Ripple Effect: Emotional Contagion and its Influence on Group Behavior,” Administrative Science Quarterly, vol. 47, no. 4, pp. 644–675, 2002. https://doi.org/10.2307/309491210.2307/3094912Search in Google Scholar

[12] World Economic Forum, “The Future of Jobs: Employment, Skills and Workforce Strategy for the Fourth Industrial Revolution,” 2016. [Online]. Available: http://www3.weforum.org/docs/WEF_FOJ_Executive_Summary_Jobs.pdf. [Accessed: Sept. 6, 2018].Search in Google Scholar

[13] S. Kaczmarek and S. Petrovica, “Promotion of Learning Motivation through Individualization of Learner-Game Interaction,” Proceedings of the IEEE Conference on Computational Intelligence and Games CIG’18, pp. 324–331, 2018. https://doi.org/10.1109/CIG.2018.849037110.1109/CIG.2018.8490371Search in Google Scholar

[14] A. Anohina and L. Intenberga, “The Set of Agents for the Modelling of Learner’s Emotions in Intelligent Tutoring Systems,” Proceedings of the 12th IASTED International Conference on Artificial Intelligence and Soft Computing, pp. 73–78, 2008.Search in Google Scholar

[15] W. G. Kennedy, “Modelling Human Behaviour in Agent-Based Models,” Agent-Based Models of Geographical Systems, Springer Netherlands, pp. 167–179, 2012. https://doi.org/10.1007/978-90-481-8927-4_910.1007/978-90-481-8927-4_9Search in Google Scholar

[16] M. Wooldridge, An Introduction to MultiAgent Systems. Second Edition: Wiley, 2009.Search in Google Scholar

[17] S. Zhang, L. Li, Z. Zhao, “Audio-visual emotion recognition based on facial expression and affective speech,” Multimedia and Signal Processing, pp. 46–52, 2012. https://doi.org/10.1007/978-3-642-35286-7_710.1007/978-3-642-35286-7_7Search in Google Scholar

[18] A. F. Botelho, R. S. Baker, and N. T. Heffernan, “Improving sensor-free affect detection using deep learning,” Proceedings of the 18th International Conference on Artificial Intelligence in Education, pp. 40–51, 2017. https://doi.org/10.1007/978-3-319-61425-0_410.1007/978-3-319-61425-0_4Search in Google Scholar

[19] B. P. Woolf, Building Intelligent Interactive Tutors. Elsevier Inc, 2009. https://doi.org/10.1016/B978-0-12-373594-2.X0001-910.1016/B978-0-12-373594-2.X0001-9Search in Google Scholar

[20] S. Petrovica, “Adaptation of Tutoring to Students’ Emotions in Emotionally Intelligent Tutoring Systems,” Proceedings of 2nd International Conference on e-Learning and e-Technologies in Education, pp. 131–136, 2013. https://doi.org/10.1109/ICeLeTE.2013.664436110.1109/ICeLeTE.2013.6644361Search in Google Scholar

[21] L. Paquette, J. Rowe, R. S. Baker, B. Mott, J. Lester, J. DeFalco, K. Brawner, R. Sottilare, and V. Georgoulas, “Sensor-Free or Sensor-Full: A Comparison of Data Modalities in Multi-Channel Affect Detection,” Proceedings of the 8th International Conference on Educational Data Mining, pp. 93–100, 2015.Search in Google Scholar

[22] M. Wixon, I. Arroyo, K. Muldner, W. Burleson, D. Rai, and B. P. Woolf, “The Opportunities and Limitations of Scaling Up Sensor-Free Affect Detection,” Proceedings of the 7th International Conference on Educational Data Mining, pp.145–152, 2014.Search in Google Scholar

[23] A. Gill, R. French, D. Gergle, and J. Oberlander, “Identifying Emotional Characteristics from Short Blog Texts,” Proceedings of the 30th Annual Conference of the Cognitive Science Society, pp. 2237–2242, 2008.10.1145/1357054.1357229Search in Google Scholar

[24] A. Kolakowska, “A review of emotion recognition methods based on keystroke dynamics and mouse movements,” Proceedings of 2013 6th International Conference on Human System Interactions, pp. 548–555, 2013. https://doi.org/10.1109/HSI.2013.657787910.1109/HSI.2013.6577879Search in Google Scholar

[25] R. Shikder, S. Rahaman, F. Afroze, and A. B. M. Alim Al Islam, “Keystroke/mouse usage based emotion detection and user identification,” Proceedings of 2017 International Conference on Networking, Systems and Security, pp. 96–104, 2017. https://doi.org/10.1109/NSysS.2017.788580810.1109/NSysS.2017.7885808Search in Google Scholar

[26] P. I. Pavlik Jr, K. W. Brawner, A. Olney, and A. Mitrovic, “A Review of Learner Models Used in Intelligent Tutoring Systems,” Design Recommendations for Intelligent Tutoring Systems - Volume 1: Learner Modeling, pp. 39–68, 2013.Search in Google Scholar

[27] K. Porayska-Pomsta and H. Pain, “Providing Cognitive and Affective Scaffolding through Teaching Strategies,” Proceedings of the 7th International Conference on Intelligent Tutoring Systems, pp. 77–86, 2004. https://doi.org/10.1007/978-3-540-30139-4_810.1007/978-3-540-30139-4_8Search in Google Scholar

[28] B. Kort, R. Reilly and R. W. Picard, “An affective model of interplay between emotions and learning: Reengineering educational pedagogy-building a learning companion,” Proceedings of IEEE International Conference on Advanced Learning Technologies, pp. 43–48, 2001. https://doi.org/10.1109/ICALT.2001.94385010.1109/ICALT.2001.943850Search in Google Scholar

[29] J. Nakamura and M. Csikszentmihalyi, “The concept of flow,” in The Handbook of Positive Psychology, C. R. Snyder & S. J. Lopez Eds. New York: Oxford University Press, 2002, pp. 89–105.Search in Google Scholar

[30] M. Gomes, T. Oliveira, F. Silva, D. Carneiro, and P. Novais, “Establishing the Relationship between Personality Traits and Stress in an Intelligent Environment”, Proceedings of the 27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, pp. 378–387, 2014. https://doi.org/10.1007/978-3-319-07467-2_4010.1007/978-3-319-07467-2_40Search in Google Scholar

[31] X. Zhou and C. Conati, “Inferring User Goals from Personality and Behavior in a Causal Model of User Affect”, Proceedings of the 8th International Conference on Intelligent User Interfaces, pp. 211–218, 2003. https://doi.org/10.1145/604045.60407810.1145/604045.604078Search in Google Scholar

[32] V. Busato, F. Prins, J. Elshout and C. Hamaker, “The Relation between Learning Styles, the Big Five Personality Traits, and Achievement Motivation in Higher Education”, Personality and Individual Differences, vol. 26, no. 1, pp. 129–140, 1999. https://doi.org/10.1016/S0191-8869(98)00112-310.1016/S0191-8869(98)00112-3Search in Google Scholar

[33] W. Kamarulzaman, “Critical Review on Effect of Personality on Learning Styles”, Proceedings of the 2nd International Conference on Arts, Social Science & Technology, pp. 12087.1–12087.7, 2012.Search in Google Scholar

[34] T. Chamorro-Premuzic, A. Furnham, and M. Lewis, “Personality and Approaches to Learning Predict Preference for Different Teaching Methods”, Learning and Individual Differences, vol. 17, no. 3, pp. 241–250, 2007. https://doi.org/10.1016/j.lindif.2006.12.00110.1016/j.lindif.2006.12.001Search in Google Scholar

[35] A. J. Elliott and H. A. McGregor, “A 2 × 2 Achievement Goal Framework,” Journal of Personality and Social Psychology, vol. 80, no. 3, pp. 501–519, 2001. https://doi.org/10.1037//0022-3514.80.3.50110.1037//0022-3514.80.3.501Search in Google Scholar

[36] S. Petrovica and A. Anohina-Naumeca, “The Adaptation Approach for Affective Game-Based Assessment,” Applied Computer Systems, vol. 22, pp.13–20, 2017. https://doi.org/10.1515/acss-2017-001310.1515/acss-2017-0013Search in Google Scholar

[37] P. Gebhard, “ALMA – A Layered Model of Affect”, AAMAS ‘05: Proceedings of the 4th International Joint Conference on Autonomous Agents and Multiagent Systemsent Systems, pp. 29–36, 2005.10.1145/1082473.1082478Search in Google Scholar

[38] C. Becker-Asano, “WASABI : Affect Simulation for Agents with Believable Interactivity,” Doctoral Thesis, Universitat Bielefeld, 2008.Search in Google Scholar

[39] T. Bosse, R. Duell, Z. A. Memon, J. Treur, J., & C. N. Van der Wal, “Agent-Based Modeling of Emotion Contagion in Groups,” Cognitive Computation, vol. 7, no. 1, pp. 111–136, 2014. https://doi.org/10.1007/s12559-014-9277-910.1007/s12559-014-9277-9Search in Google Scholar

[40] M. Pudāne, “Affective Multi-Agent System for Simulating Mechanisms of Social Effects of Emotions,” Proceedings of Seventh International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), United States of America, San Antonio, 23–26 October, pp. 129–134, 2017. https://doi.org/10.1109/ACIIW.2017.827260210.1109/ACIIW.2017.8272602Search in Google Scholar