Multiple Representations Visual Representations¶

Strategy · All strategies
Evidence · 5 claims (5 for) · 16 studies (9 causal, 4 quant-synthesis, 3 review), q2–q4 · 4 of 16 report an effect size

Description¶

This strategy presents the same content in two or more coordinated formats — typically words plus pictures, diagrams, graphs, animations, or manipulatives — rather than a single format. Learners must actively integrate the representations, mapping referents across them to construct a unified mental model. It is carried out by pairing verbal explanations with relevant visuals, sequencing them contiguously, and often supporting the mapping process with labels, color coding, or prompts.

Design Implications¶

Pairing words with meaningful graphics improves learning because verbal and visual channels process information in parallel and reinforce each other Dual coding improves recall. [+S]. The benefit is not automatic: visuals must be relevant to the learning goal, not decorative, and the combination must not exceed working memory capacity Decorative illustrations do not improve learning. [+S]. Effective use requires managing the total load across representations — splitting attention between poorly integrated formats degrades learning Cognitive overload degrades learning. [+S].

Context¶

Requirements¶

• Visuals that are relevant to the learning objective and carry instructional content, not decoration (Decorative illustrations do not improve learning. [+S])
• Spatial or temporal contiguity: corresponding words and visuals presented near each other or simultaneously
• Support for cross-referencing — labels, legends, color coding, or prompts that help learners map elements between representations
• Chunked presentation so the combined verbal + visual load stays within working memory (Chunking reduces working memory load. [+M])

Constraints¶

• Redundant on-screen text read aloud verbatim from narration can impair learning by overloading the auditory channel Cognitive overload degrades learning. [-S]
• Multiple representations impose integration costs; for novices, too many simultaneous formats can exceed working memory and depress performance Cognitive overload degrades learning. [-S]
• Learners with low prior knowledge often fail to make cross-representation mappings without explicit scaffolding; unscaffolded multiple representations can be worse than a single well-designed one [~M]
• Benefits diminish or reverse for learners with high prior knowledge, who can integrate representations on their own and may find added support redundant [~M]

Implementation Variability¶

• Static (diagrams, graphs, concept maps) vs. dynamic (animations, simulations) visuals — animation is not uniformly superior; static frames can allow learner pacing
• Multiple external representations (text + diagram) vs. multiple cases in one format, as in Cognitive Flexibility Theory
• Learner-constructed representations (drawing, graphing) vs. instructor-provided ones — construction adds generative processing but requires more support

Target Learners¶

• Novices benefit most from well-integrated word–picture pairs, which reduce the need to mentally visualize verbal descriptions Dual coding improves recall. [+S]
• Learners with low spatial ability gain disproportionately from provided visuals, which substitute for effortful mental imagery [+M]
• High-prior-knowledge learners may need fewer or leaner representations; added guidance can produce redundancy effects [~M]

Target Learning Goals¶

• Conceptual understanding of systems, processes, and spatial structures (e.g., circulatory system, chemical bonding)
• Transfer across contexts, supported by re-representing content in multiple forms Cognitive flexibility theory: multiple cases support transfer. [+M]
• Symbol fluency: mapping between graphs, equations, and real-world referents in math and science

Instructions¶

1. Identify the core concept and select a visual format that makes its structure visible (process → flow diagram; relation → graph; hierarchy → tree).
2. Write concise verbal text; avoid narrating text that duplicates on-screen words verbatim.
3. Place words and visuals contiguously — labels on the diagram, captions adjacent to figures.
4. Add mapping supports: consistent color coding, legends, or prompts asking learners to connect the representations (Analogies can bridge unfamiliar visuals to familiar ones).
5. Segment the presentation so each segment stays within working memory limits (Chunking).
6. Follow with an activity requiring learners to translate between representations (e.g., produce a graph from a description) (Application).

Related Strategies¶

• Advance Organizers — a structural visual presented before content primes integration of subsequent representations
• Analogies — a verbal representation that maps an unfamiliar domain onto a familiar visual or experiential one
• Chunking — governs how much multi-representational content can be presented at once
• Design intuitive, multisensory, layered visualizations with evolving assessment to reduce cognitive load

Examples¶

• PhET Interactive Simulations (https://phet.colorado.edu) — physics and chemistry simulations pairing dynamic visuals with adjustable parameters and short verbal prompts; learners see multiple linked representations (graph, motion, symbolic values) update simultaneously.
• Mayer's multimedia principle lessons — e.g., explaining how lightning forms with synchronized animation and narration rather than narration alone; the canonical experimental paradigm for this strategy.
• Khan Academy (https://www.khanacademy.org) — math videos pairing narrated worked procedures with dynamically drawn graphs and number lines, linking symbolic and visual forms.

Key Sources¶

• Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge University Press. doi:10.1017/CBO9780511811678
• Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198. doi:10.1016/j.learninstruc.2006.03.001
• Mayer, R. E., & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43–52. doi:10.1207/S15326985EP3801_6
• Paivio, A. (1990). Mental representations: A dual coding approach. Oxford University Press. doi:10.1093/acprof:oso/9780195066661.001.0001
• Seufert, T. (2003). Supporting coherence formation in learning from multiple representations. Learning and Instruction, 13(2), 227–237. doi:10.1016/S0959-4752(02)00022-1