What inquiry with virtual labs can learn from productive failure: A theory-driven study of students’ reflections

Charleen Brand, Jonathan Massey-Allard, Sarah Perez, Nikol Rummel, Ido Roll

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationArtificial Intelligence in Education - 20th International Conference, AIED 2019, Proceedings
EditorsSeiji Isotani, Eva Millán, Amy Ogan, Bruce McLaren, Peter Hastings, Rose Luckin
Pages30-35
Number of pages6
DOIs
StatePublished - 2019
Externally publishedYes
Event20th International Conference on Artificial Intelligence in Education, AIED 2019 - Chicago, United States
Duration: 25 Jun 201929 Jun 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11626 LNAI

Conference

Conference20th International Conference on Artificial Intelligence in Education, AIED 2019
Country/TerritoryUnited States
CityChicago
Period25/06/1929/06/19

Keywords

  • Exploratory learning environments
  • Inquiry learning
  • Invention activities
  • Productive failure
  • Virtual labs

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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