Title
Cognitive load theory vs. constructivist approaches: which best leads to efficient, deep learning?
Abbreviated Journal Title
J. Comput. Assist. Learn.
Keywords
cognitive load theory; constructivism; decision-making; integrated; knowledge; learning efficiency; WORKED EXAMPLES; KNOWLEDGE INTEGRATION; INSTRUCTIONAL-DESIGN; CLARK; 2006; ENVIRONMENTS; ARCHITECTURE; METAANALYSIS; PERFORMANCE; STRATEGIES; DISCOVERY; Education & Educational Research
Abstract
Computer-assisted learning, in the form of simulation-based training, is heavily focused upon by the military. Because computer-based learning offers highly portable, reusable, and cost-efficient training options, the military has dedicated significant resources to the investigation of instructional strategies that improve learning efficiency within this environment. In order to identify efficient instructional strategies, this paper investigates the two major learning theories that dominate the recent literature on optimizing knowledge acquisition: cognitive load theory (CLT) and constructivism. According to CLT, instructional guidance that promotes efficient learning is most beneficial. Constructivist approaches, in contrast, emphasize the importance of developing a conceptual understanding of the learning material. Supporters of these theories have debated the merits and shortcomings of both positions. However, in the absence of consensus, instructional designers lack a well-defined model for training complex skills in a rapid, efficient manner. The current study investigates the relative utility of CLT and constructivist-based approaches for teaching complex skills using a military command and control task. Findings suggest that the acquisition of procedural, declarative, and conceptual knowledge, as well as decision-making skills, did not differ as a function of the type of instruction used. However, integrated knowledge was slightly better retained by the group provided with CLT-based instruction. These results are contrary to our expectation that constructivist approaches, which focus on the development and integration of information, would yield better performance in an applied problem-based environment. Thus, while contemporary researchers continue to defend the use of constructivist strategies for teaching, our research supports earlier findings that question the utility, efficiency, and impact of these strategies in applied domains.
Journal Title
Journal of Computer Assisted Learning
Volume
27
Issue/Number
2
Publication Date
1-1-2011
Document Type
Article
Language
English
First Page
133
Last Page
145
WOS Identifier
ISSN
0266-4909
Recommended Citation
"Cognitive load theory vs. constructivist approaches: which best leads to efficient, deep learning?" (2011). Faculty Bibliography 2010s. 2050.
https://stars.library.ucf.edu/facultybib2010/2050
Comments
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