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Predicting Successful Inquiry Learning in a Virtual Performance Assessment for Science

  • Conference paper
User Modeling, Adaptation, and Personalization (UMAP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7899))

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Abstract

In recent years, models of student inquiry skill have been developed for relatively tightly-scaffolded science simulations. However, there is an increased interest in researching how video games and virtual environments can be used for both learning and assessment of science inquiry skills and practices. Such environments allow students to explore scientific content in a more open-ended context that is designed around actions and choices. In such an environment, students move an avatar around a world, speak to in-game characters, obtain objects, and take those objects to laboratories to run specific tests. While these environments allow for more autonomy and choice, assessing skills in these environments is a more difficult challenge than in closed environments or simulations. In this paper, we present models that can infer two aspects of middle-school students’ inquiry skill, from their interactive behaviors within an assessment in a virtual environment called a “virtual performance assessment” or VPA: 1) whether the student successfully demonstrates the skill of designing controlled experiments within the VPA, and 2) whether a middle-school student can successfully use their inquiry skill to determine the answer to a scientific question with a non-intuitive in-game answer.

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Baker, R.S.J.D., Clarke-Midura, J. (2013). Predicting Successful Inquiry Learning in a Virtual Performance Assessment for Science. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38844-6_17

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  • DOI: https://doi.org/10.1007/978-3-642-38844-6_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38843-9

  • Online ISBN: 978-3-642-38844-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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