Unlocking conceptual learning in mathematics and science with effective representational systems

Cheng, Peter C.-H. (1999) Unlocking conceptual learning in mathematics and science with effective representational systems. Computers & Education, 33 (2-3). pp. 109-130. ISSN 0360-1315

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Abstract

Summarizes theoretical and empirical aspects of research that is investigating how best to support conceptual learning and the critical role that representations have in complex scientific and mathematical domains. Explains Law Encoding Diagrams (LEDs) and considers how computers may further enhance the potential benefit of LEDs for conceptual learning.

Item Type: Article
Keywords: Computer Assisted Instruction, Concept Formation, Knowledge Representation, Learning Processes, Mathematics Instruction, Science Instruction
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
Depositing User: Chris Keene
Date Deposited: 11 Feb 2008
Last Modified: 17 Sep 2019 11:08
URI: http://sro.sussex.ac.uk/id/eprint/1271
Google Scholar:67 Citations
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