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Attention, Working Memory, and Long-Term Memory in Multimedia Learning: An Integrated Perspective Based on Process Models of Working Memory

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Abstract

Cognitive models of multimedia learning such as the Cognitive Theory of Multimedia Learning (Mayer 2009) or the Cognitive Load Theory (Sweller 1999) are based on different cognitive models of working memory (e.g., Baddeley 1986) and long-term memory. The current paper describes a working memory model that has recently gained popularity in basic research: the embedded-processes model (Cowan 1999). The embedded-processes model argues that working memory is not a separate cognitive system but is the activated part of long-term memory. A subset of activated long-term memory is assumed to be particularly highlighted and is termed the “focus of attention.” This model thus integrates working memory, long-term memory, and (voluntary and involuntary) attention, and referring to it within multimedia models provides the opportunity to model all these learning-relevant cognitive processes and systems in a unitary way. We make suggestions for incorporating this model into theories of multimedia learning. On this basis, one cannot only reinterpret crucial phenomena in multimedia learning that are attributed to working memory (the split-attention effect, the modality effect, the coherence effect, the signaling effect, the redundancy effect, and the expertise reversal effect) but also derive new predictions.

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Notes

  1. The finding that no modality effect is found with sequential presentation of longer texts and pictures is also in line with the assumption that long auditory texts are disadvantageous because the learner cannot skip back to previous parts of the text (transient information effect; Leahy and Sweller 2011; Wong et al. 2012).

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Schweppe, J., Rummer, R. Attention, Working Memory, and Long-Term Memory in Multimedia Learning: An Integrated Perspective Based on Process Models of Working Memory. Educ Psychol Rev 26, 285–306 (2014). https://doi.org/10.1007/s10648-013-9242-2

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