Using multimedia for e‐learning
Bibliographic Data
| ID | 23329783 |
|---|---|
| Authors | Richard E Mayer (0000-0003-4055-6938, Department of Psychological and Brain Sciences University of California CA USA, corresponding author) |
| Year | 2017 |
| Volume | 33 |
| Issue | 5 |
| Pages | 403-423 |
| Publication date | 2017-10-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Computer Assisted Learning (JOURNAL) |
| Journal identifiers | ISSN: 0266-4909 • E-ISSN: 1365-2729 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/jcal.12197 |
| OpenAlex | W2625051696 |
| Language | EN |
| Citations received | 113 |
| References cited | 123 |
This paper reviews 12 research‐based principles for how to design computer‐based multimedia instructional materials to promote academic learning, starting with the multimedia principle (yielding a median effect size of d = 1.67 based on five experimental comparisons), which holds that people learn better from computer‐based instruction containing words and graphics rather than words alone. Principles aimed at reducing extraneous processing (i.e., cognitive processing that is unrelated to the instructional objective) include coherence ( d = 0.70), signalling ( d = 0.46), redundancy ( d = 0.87), spatial contiguity ( d = 0.79) and temporal contiguity ( d = 1.30). Principles for managing essential processing (i.e., mentally representing the essential material) include segmenting ( d = 0.70), pre‐training ( d = 0.46) and modality ( d = 0.72). Principles for fostering generative processing (i.e., cognitive processing aimed at making sense of the material) include personalization ( d = 0.79), voice ( d = 0.74) and embodiment ( d = 0.36). Some principles have boundary conditions, such as being stronger for low‐ rather than high‐knowledge learners.
Cognition · Computer graphics (images) · Computer-Assisted Instruction · Contiguity · E learning · Generative grammar · Graphics · Instructional design · Multimedia · Personalization · Redundancy (engineering) · World Wide Web · Artificial Intelligence · Computer Science · Innovative Teaching and Learning Methods · Online and Blended Learning · Psychology · Visual and Cognitive Learning Processes
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| Unique citing works | 113 |
|---|---|
| Citations per year | 16,14 |
| Citation span | 2019 - 2026 (8) |
| Citation velocity | current |
| Highly cited | Yes |
| Citation types | Neutral: 107 |