Principles for managing essential processing in multimedia learning: segmenting, pre-training, and modality principles
Abstract
The split-attention principle states that in the design of instruction, including multimedia instruction, it is important to avoid materials that require learners to split their attention between, and mentally integrate, multiple sources of information. The sources of information should be both physically and temporally integrated in order to reduce unnecessary search for referents and so reduce extraneous cognitive load. Whether sources of information are intelligible in isolation, and whether the information is high in element interactivity, depends not only on the instructional material, but also on learner characteristics. Cognitive load theory, which gave rise to the split-attention principle, which is based on an understanding of human cognitive architecture, especially the relations between working and long term memory, provides theory-based and experimentally tested instructional guidelines. Those guidelines that are associated with the split-attention effect and that have been discussed in this chapter have the potential to substantially improve multimedia instruction.
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Null effects of pre-training may be attributed to specific conditions that limit its utility, such as high level of learners' prior knowledge, since learners already know the information covered during pre-training.
“Some studies have also shown that null effects of pre-training may be attributed to specific conditions that limit the utility of pre-training, such as high level of learners’ prior knowledge, since learners already know the information covered during pre-training (Mayer and Pilegard, 2014)”
From Rethinking pre-training: cognitive load implications for learners with varying prior knowledge (2025) · cites this paper as Mayer and Pilegard, 2014
Some previous studies have reported no effect of pre-training, ascribing it to boundary conditions where pre-training might not be an effective tool.
“This is inconsistent with most literature (Mayer, 2017); however, some previous studies have reported no e ff ect of pre-training (Mayer & Pilegard, 2014), ascribing it to boundary conditions where pre-training might not be an e ff ective tool.”
From Investigating the effect of pre-training when learning through immersive virtual reality and video: A media and methods experiment (2019) · cites this paper as Mayer & Pilegard, 2014
Pre-test measures of knowledge or self-efficacy could prime students in specific ways and thus influence the learning session and subsequent responses.
“A pre-test measure of self-e ffi cacy was not included based on the perspective that pre-test measures of knowledge or self-e ffi cacy could prime students in speci fi c ways and thus in fl uence the learning session and subsequent responses (Mayer, 2014).”
From Investigating the effect of pre-training when learning through immersive virtual reality and video: A media and methods experiment (2019) · cites this paper as Mayer, 2014
Mayer and Pilegard (2014) found a medium effect size of pre-training (d=0.75).
“In their review of the current literature, Mayer and Pilegard (2014) found a medium e ff ect size of pre-training ( d =0.75), while Mayer (2017) reports a more conservative e ff ect size of d = 0.46.”
From Investigating the effect of pre-training when learning through immersive virtual reality and video: A media and methods experiment (2019) · cites this paper as Mayer and Pilegard (2014)
Some previous studies have shown a large effect on knowledge when the pre-training included more extensive information on the subject taught in the learning scenario.
“While no consensus or best practice for pre-training exist, some previous studies have shown a large e ff ect on knowledge when the pre-training included more extensive information on the subject taught in the learning scenario (Mayer & Pilegard, 2014).”
From Investigating the effect of pre-training when learning through immersive virtual reality and video: A media and methods experiment (2019) · cites this paper as Mayer & Pilegard, 2014
Boundary conditions where pre-training might not be effective include cases where learners possess pre-existing knowledge of the subject, when it is more efficient to have the pre-training material presented simultaneously with the learning material, or cases where the material does not require sufficient mental effort to learn.
“These include cases where learners possess pre-existing knowledge of the subject (Mayer & Pilegard, 2014), when it is more e ffi cient to have the pre-training material presented simultaneously with the learning material; or cases where the material does not require su ffi cient mental e ff ort to learn (Kester, Kirschner, & Van Merriënboer, 2004).”
From Investigating the effect of pre-training when learning through immersive virtual reality and video: A media and methods experiment (2019) · cites this paper as Mayer & Pilegard, 2014
Pre-training often reduces intrinsic cognitive load and prepares learners for more complex tasks.
“Pre-training, in contrast, provides new but foundational information before the main learning activity, often to reduce ICL and prepare learners for more complex tasks (Mayer and Pilegard, 2014).”
From Rethinking pre-training: cognitive load implications for learners with varying prior knowledge (2025) · cites this paper as Mayer and Pilegard, 2014
Pre-training was particularly beneficial for learners with low levels of prior knowledge.
“Previous research shows that pre-training was particularly beneficial for learners with low levels of prior knowledge (Mayer and Pilegard, 2014).”
From Rethinking pre-training: cognitive load implications for learners with varying prior knowledge (2025) · cites this paper as Mayer and Pilegard, 2014
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References 70 · Cited by 212
- Authors
- Mayer, R. E., & Pilegard, C.
- Affiliations
- University of California, Santa Barbara (US)
- Corresponding author
- Mayer, Richard E.
- Venue
- The Cambridge Handbook of Multimedia Learning
- Publisher
- Cambridge University Press
- Published
- 2014-07-28
- Pages
- 316-344
- OpenAlex
- W3022206018
- Cited by
- 212
- References
- 70
- Citations by year
- 2026: 18 · 2025: 14 · 2024: 23 · 2023: 25 · 2022: 19 · 2021: 29 · 2020: 22 · 2019: 12 · 2018: 14 · 2017: 10 · 2016: 11 · 2015: 2 · 2014: 1 · 2013: 2 · 2012: 2
- FWCI
- 23.72
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Cambridge University Press eBooks (publishedVersion)
- Funders
- Office of Naval Research
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Education › Online and Blended Learning
- Keywords
- multimedia learning, cognitive load theory, segmentation, pre-training, modality principle, extraneous cognitive load, working memory, long-term memory, instructional design, element interactivity
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