O
Ouhao Chen
Researcher at Loughborough University
Publications - 27
Citations - 510
Ouhao Chen is an academic researcher from Loughborough University. The author has contributed to research in topics: Cognitive load & Interactivity. The author has an hindex of 9, co-authored 21 publications receiving 346 citations. Previous affiliations of Ouhao Chen include National Institute of Education & Southern Cross University.
Papers
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Extending Cognitive Load Theory to Incorporate Working Memory Resource Depletion: Evidence from the Spacing Effect
TL;DR: An expansion of cognitive load theory to incorporate working memory resource depletion along with instructional design implications, including the spacing effect, is discussed.
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The expertise reversal effect is a variant of the more general element interactivity effect
TL;DR: In this paper, the authors argue that the two effects may be intertwined with the expertise reversal effect constituting a particular example of the element interactivity effect, and empirical evidence is used to support this contention.
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The worked example effect, the generation effect, and element interactivity.
TL;DR: The worked example effect as mentioned in this paper indicates that examples providing full guidance on how to solve a problem result in better test performance than a problem-solving condition with no guidance, whereas the generation effect occurs when learners generating responses demonstrate better test performances than learners in a presentation condition that provides an answer.
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Relations between the worked example and generation effects on immediate and delayed tests
TL;DR: The results suggest firstly, that both the worked example and generation effects may be more likely on delayed than immediate tests and secondly, that the working example effect relies on high element interactivity material while the generation effect depends on low element interactionivity material.
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Using cognitive load theory to structure computer‐based learning including MOOCs
TL;DR: Cognitive load theory, with its roots embedded in knowledge of human cognitive architecture and evolutionary educational psychology, is ideally placed to provide instructional design principles for all forms of computer-based learning, including MOOCs, this paper suggests.