Modeling And Demonstration¶

Strategy · All strategies
Evidence · 3 claims (2 for, 1 mixed) · 4 studies (2 causal, 1 review, 1 theoretical), q3 · 0 of 4 report an effect size · 1 claim rests on one study

Description¶

Modeling and demonstration involve an expert performing a task — solving a problem, executing a procedure, applying a strategy — while learners observe. Its power comes from making thinking visible: the modeler narrates decisions, monitors their own understanding, and shows how errors are detected and corrected, rather than merely displaying the finished product.

Design Implications¶

Observing a model reduces the unguided search that overwhelms novices during initial skill acquisition Worked examples reduce unnecessary search for novices. [+M], and demonstrations that verbalize the reasoning behind actions produce better learning than silent ones [van Gog & Rummel, 2010]. Demonstration must be paired with opportunities to apply what was observed; observation alone yields shallow encoding and overconfidence Example-based sequences outperform problem-only practice for novices, and fading support is argued to aid transfer [+S].

Context¶

Requirements¶

• An accurate, complete (or deliberately partial) model of the target performance
• Narration or annotation that exposes decision points and criteria, not just actions (Think-Aloud)
• A planned follow-on activity requiring immediate application (Practice)
• Segmented presentation — pausing, chunking, or replay controls — so learners can process each step (Chunking)

Constraints¶

• Watching without applying creates an illusion of competence; learners systematically overestimate what they learned from observation Example-based sequences outperform problem-only practice for novices, and fading support is argued to aid transfer [-S]
• Overly fluent, error-free demonstrations can make performance look easier than it is; showing productive struggle and self-correction improves learners' persistence and self-efficacy [-M]
• Less effective for open-ended or creative tasks with no single correct approach
• Can anchor learners to one solution method; contrasting multiple models or including flawed examples reduces this risk
• Learners with high prior knowledge gain little and may be slowed by explicit modeling Worked-example guidance becomes less effective as learner expertise increases. [~M]

Implementation Variability¶

• Live vs. recorded: recorded demonstrations allow replay and pacing control; live modeling allows responsiveness to learner questions
• Full vs. faded: begin with complete models and progress to partial ones (Fading)
• Multiple models: presenting two or three contrasting competent models supports comparison and generalization better than a single model [~M]
• Coping models: models who struggle, err, and recover produce stronger self-efficacy gains than mastery models for anxious or low-confidence learners [~M]

Target Learners¶

• Novices encountering a skill or process for the first time Worked examples reduce unnecessary search for novices. [+M]
• Learners with low self-efficacy for the task, who benefit from seeing a peer-like model succeed (Bandura, 1977)
• Less beneficial for experts or near-experts, for whom modeling is redundant Worked-example guidance becomes less effective as learner expertise increases. [~M]

Target Learning Goals¶

• Procedural skill acquisition: learning the steps and sequence of a process
• Strategic and metacognitive skill: seeing how experts monitor, evaluate, and revise their approach
• Schema construction: building a mental model of task structure before independent problem solving

Instructions¶

1. Identify the target skill and the expert decisions it involves; script the reasoning, not just the actions.
2. Deliver the demonstration with Think-Aloud narration, segmented into digestible steps (Chunking).
3. Follow immediately with Practice on a similar task, ideally with Fading from full to partial models.
4. Include Coaching and feedback as learners attempt the task themselves.

Related Strategies¶

• Worked Examples — demonstration applied to problem solving, with written reasoning annotation
• Scaffolding — demonstration is the most supportive rung, faded as competence grows
• Direct Instruction — instructional sequence in which modeling precedes guided and independent practice

Examples¶

• Khan Academy — narrated video demonstrations of problem solving followed by practice exercises with on-demand hints.
• Codecademy — annotated code demonstrations shown inline before learners write their own version.
• Writing conferences and mentor texts — teachers model drafting and revision decisions aloud before students write, a core move in workshop-model literacy instruction.
• Cognitive Apprenticeship (Cognitive Apprenticeship) — positions modeling as the first phase, followed by coaching and articulation.

Key Sources¶

• Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84(2), 191–215. doi:10.1037/0033-295X.84.2.191
• Sweller, J., & Cooper, G. A. (1985). The use of worked examples as a substitute for problem solving in learning algebra. Cognition and Instruction, 2(1), 59–89. doi:10.1207/s1532690xci0201_3
• van Gog, T., & Rummel, N. (2010). Example-based learning: Integrating cognitive and social-cognitive research perspectives. Educational Psychology Review, 22(2), 155–174. doi:10.1007/s10648-010-9134-7
• Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, learning, and instruction (pp. 453–494). Lawrence Erlbaum. doi:10.4324/9781315044408-14
• Clark, R. C., & Mayer, R. E. (2016). E-Learning and the Science of Instruction (4th ed.). Wiley. doi:10.1002/9781119239086