Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 309

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Principles Based on Social Cues in Multimedia Learning: Personalization, Voice, Image, and Embodiment Principles

Mayer, Richard E.·2014·The Cambridge Handbook of Multimedia Learning
DOI 10.1017/cbo9781139547369.017
Open this paper in CoChat — free account

Abstract

The modality effect refers to a cognitive load learning effect that occurs when a mixed-mode (partly visual and partly auditory) presentation of information is more effective than a single-mode (either visual or auditory alone) presentation of the same information. For learning to occur, novel material must be organised and incorporated into long-term memory via a limited working memory. For instruction to be effective, it has to be designed in ways in which the limitations of working memory are overcome. As distraction and interference impose an additional memory load, their impact on the limited working memory system has to be taken into consideration in a multimedia context where the different formats of words and pictures allow for many possible ways of presenting information. The instructional predictions that flow from the experimental work on the modality effect are straightforward. From a practical perspective, the modality effect provides guidelines for effective instruction.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1017/cbo9781139547369.017

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 309

Metadata

Authors
Mayer, R. E.
Venue
The Cambridge Handbook of Multimedia Learning
Publisher
Cambridge University Press
Published
2014-07-28
Pages
345-368
DOI
10.1017/cbo9781139547369.017
OpenAlex
W298135510
Cited by
309
References
9
FWCI
24.55
Type
book chapter
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.