Visualizing¶

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

Description¶

Visualizing asks learners to construct a mental image or external representation of a problem, text, or system — a diagram, sketch, table, concept map, or mental picture — and to use that representation as a working tool for reasoning. It converts verbal or symbolic material into spatial-visual form, engaging Dual Coding Theory: information encoded both verbally and visually is better remembered and better understood than information encoded in a single channel.

Design Implications¶

Visualizing improves comprehension and problem solving because external representations offload working memory and make relational structure visible Chunking reduces working memory load. [+M]. The type of representation matters: schematic diagrams that encode the problem's relational structure support solution far better than decorative or literal pictures of surface features [~S]. Prompting learners to explain their own representations deepens the effect Self-explanation improves conceptual understanding. [+M].

Context¶

Requirements¶

• Tools for creating representations: paper and pencil, whiteboards, or software (diagramming tools, graphing calculators, concept-mapping apps)
• Tasks whose structure benefits from spatial or relational depiction (systems, processes, quantitative relationships, narratives)
• Instruction in what to represent — learners need to know which features of a problem the diagram must capture, not merely be told to "draw it"

Constraints¶

• Learners who draw literal, pictorial images of surface details rather than schematic representations of relations show no benefit and sometimes perform worse [~S] — young children and low-prior-knowledge learners are especially prone to this
• Visualizing abstract concepts with no natural spatial structure can force misleading metaphors and impair reasoning
• Producing a representation adds production load; for novices, poorly scaffolded drawing tasks can consume capacity needed for the underlying reasoning [-M]
• Benefits diminish for learners with strong prior knowledge who already hold efficient internal representations [~M]

Implementation Variability¶

• Learner-generated (drawing, mapping) versus instructor-provided (worked diagrams, animations) representations; learner-generated generally produces deeper processing but requires more scaffolding
• Mental visualization (imagery prompts) versus external drawing; external products are easier to assess and revise
• Domain-specific formats: force diagrams in physics, tape diagrams in mathematics, story maps in reading, concept maps in biology

Target Learners¶

• Novices and low-prior-knowledge learners, for whom an external representation substitutes for a still-unformed internal model [+M]
• Learners solving multi-step quantitative problems, where diagrams reduce transcription and search errors
• Less beneficial for experts, who may find mandated drawing redundant [~M]

Target Learning Goals¶

• Comprehension of texts, systems, and processes with relational structure
• Problem solving: representing a problem correctly is the strongest predictor of solving it correctly
• Retention, via dual verbal–visual encoding

Instructions¶

1. Model the construction of a representation for a worked problem, narrating which features you encode and why — Demonstration
2. Present a similar problem and prompt learners to build their own representation before computing or writing an answer — Practice
3. Have learners compare representations against a target schematic and explain differences — Provide Feedback combined with self-explanation
4. Fade the prompting as learners adopt visualization spontaneously

Related Strategies¶

• Annotating — text-marking is a lightweight form of external representation
• Drawing to Learn — the science-classroom variant of learner-generated visualization
• Concept Mapping — node-link visualization of relational knowledge
• Choose problems with multiple entry points to stimulate discussion of different solution approaches
• Prompt students to sketch a drawing of the system while reading an expository science text

Related Elements¶

• Demonstration — modeling how to construct a representation
• Practice — repeated representation-building across varied problems
• Provide Feedback — correcting pictorial-but-unschematic representations

Examples¶

• Singapore Mathematics (https://www.moe.gov.sg) — the bar-model method has students draw rectangular bars representing quantities and relationships before solving word problems; the drawing is the solution strategy, not decoration.
• Physics education "sketch the situation" prompts — standard practice in curricula such as Tutorials in Introductory Physics (McDermott & Shaffer, University of Washington), where force and motion diagrams precede equations.
• Reading comprehension story maps — learners diagram setting, characters, and causal chains while reading narrative text.

Key Sources¶

• Mayer, R. E. (2009). Multimedia Learning (2nd ed.). Cambridge University Press. doi:10.1017/cbo9780511811678
• Hegarty, M., & Kozhevnikov, M. (1999). Types of visual–spatial representations and mathematical problem solving. Journal of Educational Psychology, 91(4), 684–689. doi:10.1037/0022-0663.91.4.684
• van Garderen, D., & Montague, M. (2003). Visual–spatial representation, mathematical problem solving, and students of varying abilities. Learning Disabilities Research & Practice, 18(4), 246–254.
• Fiorella, L., & Mayer, R. E. (2016). Eight ways to promote generative learning. Educational Psychology Review, 28(4), 717–741. doi:10.1007/s10648-015-9348-9