Abstract
In the context of an educational virtual world to assist students to gain research inquiry skills, we are seeking to use Animated Pedagogical Agents (APAs) to capture students’ emotional states and provide motivational support. We have conducted a classroom study involving an Educational Virtual World for acquiring and testing knowledge of biological concepts and science inquiry skills with a total of 30 students in Years 8–9 at a co-educational selective school. To ascertain their emotional feelings while using the VW, students encountered five APAs who greeted them by inquiring “How are you?” We found students were generally willing to disclose their emotional feeling and there were differences in emotions reported based on gender. The approach captures emotions during learning but is minimally disruptive and could aid relationship development with the APA while providing a means to validate other emotion elicitation methods.
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References
Shen, L., Wang, M., Shen, R.: Affective e-learning: Using “emotional” data to improve learning in pervasive learning environment. J. Educ. Technol. Soc. 12(2), 176 (2009)
Arguel, A., Lane, R.: Fostering deep understanding in geography by inducing and managing confusion: an online learning approach (2015)
Ranjbartabar, H., Richards, D.: Student designed virtual teacher feedback. In: Proceedings of the 9th International Conference on Computer and Automation Engineering. ACM (2017)
Arguel, A., et al.: Inside out: detecting learners’ confusion to improve interactive digital learning environments. J. Educ. Comput. Res. 55(4), 526–551 (2017)
Sabourin, J., Mott, B., Lester, J.: Computational models of affect and empathy for pedagogical virtual agents. In: Standards in Emotion Modeling, Lorentz Center International Center for Workshops in the Sciences (2011)
Johnson, W.L., Rickel, J.W., Lester, J.C.: Animated pedagogical agents: Face-to-face interaction in interactive learning environments. Int. J. Artif. Intell. Educ. 11(1), 47–78 (2000)
Burleson, W.: Affective learning companions: strategies for empathetic agents with real-time multimodal affective sensing to foster meta-cognitive and meta-affective approaches to learning, motivation, and perseverance. Massachusetts Institute of Technology (2006)
D’Mello, S., Calvo, R.A.: Beyond the basic emotions: what should affective computing compute?. In: CHI 2013 Extended Abstracts on Human Factors in Computing Systems. ACM (2013)
Gwo-Dong, C., et al.: An empathic avatar in a computer-aided learning program to encourage and persuade learners. J. Educ. Technol. Soc. 15(2), 62 (2012)
Robison, J.L., Mcquiggan, S.W., Lester, J.C.: Modeling task-based vs. Affect-based feedback behavior in pedagogical agents: an inductive approach. In: AIED (2009)
Schertz, M.: Empathic pedagogy: community of inquiry and the development of empathy. Anal. Teach. 26(1), 8–14 (2006)
Kort, B., Reilly, R., Picard, R.W.: An affective model of interplay between emotions and learning: reengineering educational pedagogy-building a learning companion. In: 2001 Proceedings of the IEEE International Conference on Advanced Learning Technologies. IEEE (2001)
Paiva, A., et al.: Learning by feeling: evoking empathy with synthetic characters. Appl. Artif. Intell. 19(3–4), 235–266 (2005)
Kapur, M.: Productive failure. Cogn. Instr. 26(3), 379–424 (2008)
Acknowledgement
We would like to thank the participants in our study. Also, we thank Meredith Taylor for her assistance with Omosa. This work has in part been supported by Australian Research Council Discovery Project DP150102144.
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Ranjbartabar, H., Richards, D., Makhija, A., Jacobson, M.J. (2018). Students’ Responses to a Humanlike Approach to Elicit Emotion in an Educational Virtual World. In: Penstein Rosé, C., et al. Artificial Intelligence in Education. AIED 2018. Lecture Notes in Computer Science(), vol 10948. Springer, Cham. https://doi.org/10.1007/978-3-319-93846-2_54
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DOI: https://doi.org/10.1007/978-3-319-93846-2_54
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