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ERIC Number: EJ791104
Record Type: Journal
Publication Date: 2008-Jun
Pages: 22
Abstractor: Author
Reference Count: N/A
ISBN: N/A
ISSN: ISSN-1042-1629
Designing Effective Supports for Causal Reasoning
Jonassen, David H.; Ionas, Ioan Gelu
Educational Technology Research and Development, v56 n3 p287-308 Jun 2008
Causal reasoning represents one of the most basic and important cognitive processes that underpin all higher-order activities, such as conceptual understanding and problem solving. Hume called causality the "cement of the universe" [Hume (1739/2000). Causal reasoning is required for making predictions, drawing implications and inferences, and explaining phenomena. Causal relations are usually more complex than learners understand. In order to be able to understand and apply causal relationships, learners must be able to articulate numerous covariational attributes of causal relationships, including direction, valency, probability, duration, responsiveness, as well as mechanistic attributes, including process, conjunctions/disjunctions, and necessity/sufficiency. We describe different methods for supporting causal learning, including influence diagrams, simulations, questions, and different causal modeling tools, including expert systems, systems dynamics tools, and causal modeling tools. Extensive research is needed to validate and contrast these methods for supporting causal reasoning.
Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: Researchers
Language: English
Sponsor: N/A
Authoring Institution: N/A