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Articles

Supporting students' learning in the domain of computer science

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Pages 1-28 | Received 29 Nov 2009, Accepted 01 Jul 2010, Published online: 30 Mar 2011
 

Abstract

Previous studies have shown that students with low knowledge understand and learn better from more cohesive texts, whereas high-knowledge students have been shown to learn better from texts of lower cohesion. This study examines whether high-knowledge readers in computer science benefit from a text of low cohesion. Undergraduate students (n = 65) read one of four versions of a text concerning Local Network Topologies, orthogonally varying local and global cohesion. Participants' comprehension was examined through free-recall measure, text-based, bridging-inference, elaborative-inference, problem-solving questions and a sorting task. The results indicated that high-knowledge readers benefited from the low-cohesion text. The interaction of text cohesion and knowledge was reliable for the sorting activity, for elaborative-inference and for problem-solving questions. Although high-knowledge readers performed better in text-based and in bridging-inference questions with the low-cohesion text, the interaction of text cohesion and knowledge was not reliable. The results suggest a more complex view of when and for whom textual cohesion affects comprehension and consequently learning in computer science.

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