Can Cognitive Style Predict How Individuals Use Web-Based Learning Environments?

Can Cognitive Style Predict How Individuals Use Web-Based Learning Environments?

Martin Graff (University of Glamorgan, UK)
DOI: 10.4018/978-1-60566-392-0.ch003
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This chapter considers the question of whether Web-based learning environments can be employed to effectively facilitative learning. Several questions are considered around this issue, principally whether variations in hypertext architecture, and individual differences in information processing are salient factors for consideration. Furthermore, whether the effectiveness of learning depends precisely upon how learning is defined. Finally, differences in hypertext navigational strategies are assessed in terms of whether these can be predicted by individual differences in cognitive style. The chapter ends by concluding that the research on Web-based instructional systems is to some extent promising, although the field of cognitive style is diverse, and realistic predictions regarding the use of this construct in instructional design is, as yet, tenuous.
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Web-Based Learning And Hypertext Architecture

A useful starting point would be to question whether using different hypertext structures differentially affect learning performance. The earlier studies considering this question seem to suggest that mixed or relational web-based or hypertext systems appear to be the most facilitative.

For instance in a study by Mohageg (1982) the issue of whether question answering performance would vary following delivery of learning materials via three different web structures or architectures was considered. The architectures used in this study were hierarchical, where the learning material was constructed such that more general information was contained higher up the structure, and more specific information lower down; network, where the information was structured in a complex system of links; and mixed which was a combination of the other two structures. The findings indicated that learning performance was poorest in the network architecture condition. However, there were no differences in learning performance in the other conditions. The interpretation of this finding was that as the mixed condition featured more links than the other conditions, this may have increased the learners’ facility for learning.

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