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“Thanks Alisha, Keep in Touch”: Gender Effects and Engagement with Virtual Learning Companions

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Artificial Intelligence in Education (AIED 2017)

Abstract

Virtual learning companions have shown significant potential for supporting students. However, there appear to be gender differences in their effectiveness. In order to support all students well, it is important to develop a deeper understanding of the role that student gender plays during interactions with learning companions. This paper reports on a study to explore the impact of student gender and learning companion design. In a three-condition study, we examine middle school students’ interactions in a game-based learning environment that featured one of the following: (1) a learning companion deeply integrated into the narrative of the game; (2) a learning companion whose backstory and personality were not integrated into the narrative but who provided equivalent task support; and (3) no learning companion. The results show that girls were significantly more engaged than boys, particularly with the narrative-integrated agent, while boys reported higher mental demand with that agent. Even when controlling for video game experience and prior knowledge, the gender effects held. These findings contribute to the growing understanding that learning companions must adapt to students’ gender in order to facilitate the most effective learning interactions.

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Acknowledgements

The authors are grateful for the thoughtful input of the members of the LearnDialogue group. This work is supported by the National Science Foundation through grant CHS-1409639. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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Correspondence to Lydia G. Pezzullo .

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Pezzullo, L.G. et al. (2017). “Thanks Alisha, Keep in Touch”: Gender Effects and Engagement with Virtual Learning Companions. In: André, E., Baker, R., Hu, X., Rodrigo, M., du Boulay, B. (eds) Artificial Intelligence in Education. AIED 2017. Lecture Notes in Computer Science(), vol 10331. Springer, Cham. https://doi.org/10.1007/978-3-319-61425-0_25

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  • DOI: https://doi.org/10.1007/978-3-319-61425-0_25

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