Abstract
Pedagogical agents have been shown to be highly effective for supporting learning in a broad range of contexts, including game-based learning. However, there are key open questions around how to design dialogue policies for pedagogical agents that support students in game-based learning environments. This paper reports on a study to investigate two different agent dialogue policies with regard to conversational initiative, a core consideration in dialogue system design. In the User Initiative policy, only the student could initiate conversations with the agent, while in the Mixed Initiative policy, both the agent and the student could initiate conversations. In a study with 67 college students, results showed that the Mixed Initiative policy not only promoted more conversation, but also better supported the goals of the game-based learning environment by fostering exploration, yielding better performance on in-game assessments, and creating higher student engagement.
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References
Abdullah, A., et al.: Pedagogical agents to support embodied, discovery-based learning. Intelligent Virtual Agents. LNCS (LNAI), vol. 10498, pp. 1–14. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67401-8_1
Al Moubayed, S., Lehman, J.: Regulating turn-taking in multi-child spoken interaction. In: Brinkman, W.-P., Broekens, J., Heylen, D. (eds.) IVA 2015. LNCS (LNAI), vol. 9238, pp. 363–374. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-21996-7_40
Borjigin, A., Miao, C., Lim, S.F., Li, S., Shen, Z.: Teachable agents with intrinsic motivation. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M.F. (eds.) AIED 2015. LNCS (LNAI), vol. 9112, pp. 34–43. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19773-9_4
D’mello, S., Graesser, A.: Autotutor and affective AutoTutor: learning by talking with cognitively and emotionally intelligent computers that talk back. ACM Trans. Interact. Intell. Syst. (TiiS) 2(4), 23 (2012)
Girard, S., et al.: Defining the behavior of an affective learning companion in the affective meta-tutor project. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds.) AIED 2013. LNCS (LNAI), vol. 7926, pp. 21–30. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-39112-5_3
Hart, S.G., Staveland, L.E.: Development of NASA-TLX (task load index): results of empirical and theoretical research. Adv. Psychol. 52, 139–183 (1988)
Jurafsky, D., Martin, J.: Dialog systems and chatbots. In: Speech and Language Processing (2017)
O’Brien, H.L., Toms, E.G.: The development and evaluation of a survey to measure user engagement. J. Am. Soc. Inf. Sci. Technol. 61(1), 50–69 (2010)
Panaite, M., et al.: Bring it on! Challenges encountered while building a comprehensive tutoring system using ReaderBench. In: Penstein Rosé, C., et al. (eds.) AIED 2018. LNCS (LNAI), vol. 10947, pp. 409–419. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93843-1_30
Ternblad, E.M., Haake, M., Anderberg, E., Gulz, A.: Do preschoolers ‘Game the System’? A case study of children’s intelligent (mis)use of a teachable agent based play-&-learn game in mathematics. In: Penstein Rosé, C., et al. (eds.) AIED 2018. LNCS (LNAI), vol. 10947. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-93843-1_41
Wiggins, J.B., et al.: User affect and no-match dialogue scenarios: an analysis of facial expression. In: Proceedings of the 4th International Workshop on Multimodal Analyses Enabling Artificial Agents in Human-Machine Interaction, pp. 6–14. ACM (2018)
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This research was funded by the National Science Foundation under grants DRL-1721160 and IIS-1409639. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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Wiggins, J.B. et al. (2019). Take the Initiative: Mixed Initiative Dialogue Policies for Pedagogical Agents in Game-Based Learning Environments. In: Isotani, S., Millán, E., Ogan, A., Hastings, P., McLaren, B., Luckin, R. (eds) Artificial Intelligence in Education. AIED 2019. Lecture Notes in Computer Science(), vol 11626. Springer, Cham. https://doi.org/10.1007/978-3-030-23207-8_58
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