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Abstract

Minecraft continues to be a popular digital game throughout the world, and the ways in which adolescents play can provide insight into their existing interests. Through informal summer camps using Minecraft to expose middle school students to concepts in astronomy and earth science, we collected self-reports of STEM and Minecraft interest, as well as behavioral log data through player in-game interactions. Finding relationships between in-game behaviors and individual interest can provide insight into how educational experiences in digital games might be designed to support learner interests and competencies in STEM. Bayesian model averaging of data across camps was implemented to address the relatively small sample size of the data. Results revealed the important role of existing interest and knowledge for developing and sustaining interest.

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Correspondence to Matthew Gadbury .

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Gadbury, M., Chad Lane, H. (2023). A Bayesian Analysis of Adolescent STEM Interest Using Minecraft. In: Wang, N., Rebolledo-Mendez, G., Dimitrova, V., Matsuda, N., Santos, O.C. (eds) Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky. AIED 2023. Communications in Computer and Information Science, vol 1831. Springer, Cham. https://doi.org/10.1007/978-3-031-36336-8_60

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  • DOI: https://doi.org/10.1007/978-3-031-36336-8_60

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36335-1

  • Online ISBN: 978-3-031-36336-8

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