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Author: Luděk Kučera

Affiliation: Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic, Faculty of Information Technologies, Czech Technical University, Prague, Czech Republic

ISBN: 978-989-758-417-6

Keyword(s): Visualization, Algorithm, Invariant, JavaScript, Computer-supported Education, Social Aspect.

Abstract: The present paper tries to point out two aspects of the computer supported education at the university level. The first aspect relates to cognition, in particular to methods of computer support of learning difficult concepts in natural sciences, computer science, and engineering, like mathematical notions and theorems, physical laws, and complex algorithms and their behavior. The second aspect is social - only few papers describe how the new educational methods are or have been accepted by the community, whether they finished as a single experiment at the authors’ institution or whether they are used in other schools, how difficult is spreading them out and what kind of obstacles the authors meet. We feel that even quite successful projects face certain inertia of the school system and the community of teachers that make the wider use of new methods complicated.

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Paper citation in several formats:
Kučera, L. (2020). Cognitive and Social Aspects of Visualization in Algorithm Learning.In Proceedings of the 12th International Conference on Computer Supported Education - Volume 2: CSEDU, ISBN 978-989-758-417-6, pages 270-277. DOI: 10.5220/0009359102700277

@conference{csedu20,
author={Luděk Kučera.},
title={Cognitive and Social Aspects of Visualization in Algorithm Learning},
booktitle={Proceedings of the 12th International Conference on Computer Supported Education - Volume 2: CSEDU,},
year={2020},
pages={270-277},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009359102700277},
isbn={978-989-758-417-6},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Computer Supported Education - Volume 2: CSEDU,
TI - Cognitive and Social Aspects of Visualization in Algorithm Learning
SN - 978-989-758-417-6
AU - Kučera, L.
PY - 2020
SP - 270
EP - 277
DO - 10.5220/0009359102700277

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