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DynaLearn — An Intelligent Learning Environment for Learning Conceptual Knowledge

Authors:

Floris Linnebank,

Michael Wiβner,

René Bühling,

Petya Borisova,

David MioduserAuthors Info & Claims

AI Magazine, Volume 34, Issue 4

Pages 46 - 65

https://doi.org/10.1609/aimag.v34i4.2489

Published: 01 December 2013 Publication History

Abstract

Articulating thought in computer‐based media is a powerful means for humans to develop their understanding of phenomena. We have created DynaLearn, an intelligent learning environment that allows learners to acquire conceptual knowledge by constructing and simulating qualitative models of how systems behave. DynaLearn uses diagrammatic representations for learners to express their ideas. The environment is equipped with semantic technology components that are capable of generating knowledge‐based feedback and virtual characters that enhance the interaction with learners. Teachers have created course material, and successful evaluation studies have been performed. This article presents an overview of the DynaLearn system.

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Information & Contributors

Information

Published In

cover image AI Magazine

AI Magazine Volume 34, Issue 4

Winter 2013

126 pages

ISSN:0738-4602

EISSN:2371-9621

DOI:10.1002/aaai.v34.4

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© 2013 The Authors. AI Magazine published by John Wiley & Sons Ltd on behalf of Association for the Advancement of Artificial Intelligence.

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John Wiley & Sons, Inc.

United States

American Association for Artificial Intelligence

United States

Publication History

Published: 01 December 2013

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Cited By

Kragten MBredeweg BHong JPark J(2024)The effectiveness of lightweight automated support for learning about dynamic systems with qualitative representationsProceedings of the 39th ACM/SIGAPP Symposium on Applied Computing10.1145/3605098.3635950(11-20)Online publication date: 8-Apr-2024
https://dl.acm.org/doi/10.1145/3605098.3635950
Kragten MHoogma TBredeweg B(2024)Integration of a Teacher Dashboard in a Hybrid Support Approach for Constructing Qualitative RepresentationsTechnology Enhanced Learning for Inclusive and Equitable Quality Education10.1007/978-3-031-72315-5_15(208-221)Online publication date: 16-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-72315-5_15
Kragten MBredeweg B(2024)Calcium Regulation Assignment: Alternative Styles in Successfully Learning About Biological MechanismsArtificial Intelligence in Education10.1007/978-3-031-64302-6_16(220-234)Online publication date: 8-Jul-2024
https://dl.acm.org/doi/10.1007/978-3-031-64302-6_16
Blasch ECruise RAved AMajumder URovito T(2019)Methods of AI for Multimodal Sensing and Action for Complex SituationsAI Magazine10.1609/aimag.v40i4.481340:4(50-65)Online publication date: 1-Dec-2019
https://dl.acm.org/doi/10.1609/aimag.v40i4.4813
Kolodner J(2015)Cognitive Prosthetics for Fostering LearningAI Magazine10.1609/aimag.v36i4.261536:4(34-50)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1609/aimag.v36i4.2615

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