Pictures & Visuals¶

Strategy · All strategies
Evidence · 3 claims (1 for, 2 against) · 11 studies (7 causal, 3 quant-synthesis, 1 review), q2–q4 · 3 of 11 report an effect size

Description¶

This strategy uses images, diagrams, videos, animations, and graphic organizers to represent content alongside or instead of verbal explanation. Its theoretical basis is Dual Coding Theory: information encoded both verbally and visually leaves two retrieval paths, improving recall Pairing words with relevant images improves recall compared with words alone. [+S]. The benefit is conditional, not automatic — visuals help when they are relevant, explanatory, and integrated with text, and can harm learning when they are decorative or overloaded Decorative illustrations do not improve learning and can reduce it by diverting attention. [-S].

Design Implications¶

Visuals work by directing attention to essential content, making abstract or invisible structures concrete, and providing a second memory code. The multimedia principle — presenting words and pictures together rather than words alone — reliably improves transfer when the picture is explanatory Mayer's multimedia principle research shows illustrations foster deeper understanding than text alone. [+S]. But every visual competes for limited working memory; irrelevant or redundant graphics impose extraneous load Cognitive overload degrades learning when working memory demands exceed capacity. [-S]. The design question is never "should I add a picture?" but "does this picture explain something the words alone cannot?"

Context¶

Requirements¶

• Visuals that are relevant to the learning objective — explanatory (diagrams, process illustrations, concept sketches), not merely attractive
• Integration of visual and verbal channels: captions, labels, and placement near the corresponding text (Chunking of complex visuals into sequential displays)
• Alignment with Cognitive Load Management: strip decorative clutter, highlight essential features, and avoid presenting identical text verbatim on screen and in narration

Constraints¶

• Decorative stock images, clip art, and "engaging" photos do not improve learning and can reduce it by splitting attention Decorative illustrations do not improve learning and can reduce it by diverting attention. [-S]
• Overly complex or dense visuals (busy diagrams, animations with excessive motion) overload the visual channel Cognitive overload degrades learning when working memory demands exceed capacity. [-S]
• Redundancy harms learning: full on-screen text duplicating narration consumes the same channel and reduces comprehension [~S]
• Learners with low prior knowledge benefit most from well-designed visuals; experts may find them redundant [~M]

Implementation Variability¶

• Static vs. animated: animation helps only for content involving continuous change (e.g., circulatory flow); static diagrams with stepwise presentation often outperform animation for complex systems [~M]
• Learner-generated visuals: having students draw or build their own representations (sketchnoting, concept sketches) can outperform viewing, because generation forces deeper processing [+M]
• Graphic organizers: advance organizers and structured diagrams frame incoming information; see Advance Organizers
• Annotated visuals: learner or instructor markup on diagrams directs attention; see Annotating

Target Learners¶

• Novices, who lack the prior knowledge to generate their own mental imagery from verbal description alone [+M]
• Young learners and second-language learners, for whom visuals reduce the verbal comprehension burden
• Less beneficial for experts, who already hold adequate mental models and may find explanatory visuals redundant [~M]

Target Learning Goals¶

• Recall and retention of factual and conceptual content Pairing words with relevant images improves recall compared with words alone. [+S]
• Comprehension of systems, processes, and spatial relationships (anatomy, circuits, maps, workflows)
• Vocabulary development through image-mediated meaning
• Transfer of principles to new situations, when visuals illustrate underlying structure rather than surface detail [+M]

Instructions¶

1. Identify the core concept the visual must explain; reject any image that does not map onto the learning objective.
2. Select or design an explanatory visual — diagram, illustration, or animation — that makes structure or process visible.
3. Integrate words and pictures closely: label parts, place captions adjacent to the relevant visual region, and avoid redundant verbatim text.
4. Sequence complex visuals in Chunking steps rather than presenting everything at once.
5. Pair viewing with active processing — labeling, predicting, drawing, or explaining — via Practice or Demonstration.
6. Assess understanding by having learners interpret, complete, or produce visuals, not just recognize them.

Related Strategies¶

• Analogies — visual analogies map unfamiliar structures onto familiar ones
• Advance Organizers — visual frameworks presented before content
• Annotating — marking up visuals directs attention to essential features
• STeLLA® teaching strategies for explaining, identifying, and engaging science concepts

Related Elements¶

• Demonstration — visuals that model a process step by step
• Practice — active tasks that force learners to use the visual representation
• Advance Organizers — a visual framing device for new content

Tools¶

• InferCabulary (https://www.infercabulary.com) — teaches vocabulary by presenting multiple images from which learners infer meaning
• Canva / Adobe Express — for designing clean, low-clutter instructional graphics
• PhET Interactive Simulations (https://phet.colorado.edu) — interactive visual simulations of science and math concepts
• BioDigital / Visible Body — 3D anatomical visuals replacing dense verbal description

Examples¶

• A biology teacher replaces a text-only explanation of photosynthesis with a labeled, stepwise diagram that students annotate and then redraw from memory, exploiting dual coding for retention [+S].
• A statistics instructor uses PhET simulations to let learners manipulate sample size and watch the sampling distribution change, making an abstract concept manipulable.
• A vocabulary program like InferCabulary presents several related images per word, prompting learners to infer the shared meaning rather than memorize a definition.
• A negative case: a slide deck decorated with unrelated stock photos shows no learning benefit and slightly reduces recall compared with text-only slides [-S].

Key Sources¶

• Mayer, R. E. (2021). Multimedia learning (3rd ed.). Cambridge University Press. doi:10.1017/9781316941355
• Mayer, R. E. (1989). Systematic thinking fostered by illustrations in text. Journal of Educational Psychology, 81(4), 615–623. doi:10.1037/0022-0663.81.2.240
• Carney, R. N., & Levin, J. R. (2002). Pictorial illustrations still improve students' learning from text. Educational Psychology Review, 14(1), 5–26. doi:10.1023/a:1013176309260
• Paivio, A. (1990). Mental representations: A dual coding approach. Oxford University Press. doi:10.1093/acprof:oso/9780195066661.001.0001
• Clark, R. C., & Mayer, R. E. (2016). E-Learning and the Science of Instruction (4th ed.). Wiley. doi:10.1002/9781119239086