@inproceedings{d5e62af4a9284d3ab6ca511971e9904a,
title = "A Bayesian Analysis of Adolescent STEM Interest Using Minecraft",
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.",
keywords = "Bayesian analysis, Digital games, informal learning, interest",
author = "Matthew Gadbury and {Chad Lane}, H.",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 24th International Conference on Artificial Intelligence in Education , AIED 2023 ; Conference date: 03-07-2023 Through 07-07-2023",
year = "2023",
doi = "10.1007/978-3-031-36336-8_60",
language = "English (US)",
isbn = "9783031363351",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "384--389",
editor = "Ning Wang and Genaro Rebolledo-Mendez and Vania Dimitrova and Noboru Matsuda and Santos, {Olga C.}",
booktitle = "Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky - 24th International Conference, AIED 2023, Proceedings",
address = "Germany",
}