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What Inquiry with Virtual Labs Can Learn from Productive Failure: A Theory-Driven Study of Students’ Reflections

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Artificial Intelligence in Education (AIED 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11626))

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Abstract

During inquiry learning with virtual labs students are invited to construct mathematical models that capture key features of the underlying structures. However, students typically fail to construct complete models. In order to identify ways to support learners without restricting them, we look at the literature of Productive Failure and Invention activities (often termed PS-I, Problem Solving before Instruction). PS-I activities are designed to facilitate specific cognitive mechanisms that aid learning. This paper seeks to (1) evaluate in what ways PS-I activities compare to inquiry learning, (2) whether students in inquiry learning report similar processes to PS-I, and (3) whether these are associated with better learning. We begin by synthesizing the two approaches in order to highlight their similarities. Following, we coded self-reported post-activity reflections by 139 students who worked with two virtual labs. Students reported processes that are typical to PS-I and, out of these, prior knowledge activation was associated with constructing more complete models. Based on this, we suggest ways to support students in learning from their inquiry.

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Correspondence to Charleen Brand .

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Brand, C., Massey-Allard, J., Perez, S., Rummel, N., Roll, I. (2019). What Inquiry with Virtual Labs Can Learn from Productive Failure: A Theory-Driven Study of Students’ Reflections. 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_6

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  • DOI: https://doi.org/10.1007/978-3-030-23207-8_6

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