Searching for buried treasure: uncovering discovery in discovery-based learning

Searching for buried treasure: uncovering discovery in discovery-based learning Forty 4th and 9th grade students participated individually in tutorial interviews centered on a problem-solving activity designed for learning basic algebra mechanics through diagrammatic modeling of an engaging narrative about a buccaneering giant burying and unearthing her treasure on a desert island. Participants were randomly assigned to experimental (Discovery) and control (No-Discovery) conditions. Mixed-method analyses revealed greater learning gains for Discovery participants. Elaborating on a heuristic activity architecture for technology-based guided-discovery learning (Chase and Abrahamson 2015), we reveal a network of interrelated inferential constraints that learners iteratively calibrate as they each refine and reflect on their evolving models. We track the emergence of these constraints by analyzing annotated transcriptions of two case-study student sessions and argue for their constituting role in conceptual development. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Instructional Science Springer Journals

Searching for buried treasure: uncovering discovery in discovery-based learning

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media B.V., part of Springer Nature
Subject
Education; Learning and Instruction; Educational Psychology; Pedagogic Psychology
ISSN
0020-4277
eISSN
1573-1952
D.O.I.
10.1007/s11251-017-9433-1
Publisher site
See Article on Publisher Site

Abstract

Forty 4th and 9th grade students participated individually in tutorial interviews centered on a problem-solving activity designed for learning basic algebra mechanics through diagrammatic modeling of an engaging narrative about a buccaneering giant burying and unearthing her treasure on a desert island. Participants were randomly assigned to experimental (Discovery) and control (No-Discovery) conditions. Mixed-method analyses revealed greater learning gains for Discovery participants. Elaborating on a heuristic activity architecture for technology-based guided-discovery learning (Chase and Abrahamson 2015), we reveal a network of interrelated inferential constraints that learners iteratively calibrate as they each refine and reflect on their evolving models. We track the emergence of these constraints by analyzing annotated transcriptions of two case-study student sessions and argue for their constituting role in conceptual development.

Journal

Instructional ScienceSpringer Journals

Published: Nov 9, 2017

References

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