Interactive learning experiences
Design simulations and interactives that help learners test ideas, receive meaningful feedback and build understanding.
Overview
An interactive learning experience responds to learner action. It may allow learners to manipulate variables, make choices, construct a representation, test a prediction, navigate a scenario or receive feedback.
Interactivity is not valuable simply because a learner clicks, drags or selects. The educational value depends on the relationship between the action, the representation, the feedback and the knowledge or skill being developed.
Relevance to teaching and learning
Interactive experiences can make systems and consequences visible, support repeated experimentation, compress or expand time, and allow learners to test ideas without the cost or risk of a real setting.
They can also create productive opportunities for dialogue: learners may predict before acting, compare outcomes, explain patterns and revise models. Used poorly, however, an interactive can become a sequence of trial-and-error clicks, a game of finding the expected answer or an overloaded interface that hides the target idea.
Key ideas
- Define the productive action. Identify what the learner should manipulate, decide, construct or explain.
- Make the system legible. Learners need to understand what can be changed, what is being represented and what counts as evidence.
- Couple action and consequence. Feedback should reveal meaningful relationships rather than merely announce correctness.
- Invite prediction and explanation. Prompts before and after action can turn exploration into reasoning.
- Use constraints deliberately. Limit options when unrestricted exploration would overwhelm novices; open the system as understanding grows.
- Support iteration. Allow learners to retry, compare cases and observe changes without excessive reset cost.
- Design for facilitation. Provide teachers with learning goals, likely misconceptions, discussion prompts and ways to connect the interactive to other lesson phases.
- Evaluate learning, not engagement alone. Measure changes in explanation, strategy, transfer or performance rather than time-on-task and enjoyment only.
Use cases and examples
- A science simulation in which students vary one factor, predict an outcome and compare results to a model.
- A historical decision scenario that asks learners to weigh evidence and consequences rather than choose a single decontextualised answer.
- A mathematics interactive that externalises relationships among graphical, numerical and symbolic representations.
- A professional-learning simulation that allows educators to rehearse classroom decisions and reflect on alternative responses.
Limitations and implementation cautions
- Open exploration can produce superficial play when goals and prompts are absent.
- Immediate correctness feedback can encourage answer seeking rather than explanation.
- Interfaces may favour students who already understand the representation conventions.
- A simulation cannot replace physical practice when handling real equipment, materials or social complexity is itself part of the learning objective.
Evidence
Research on simulation-based learning generally supports its potential for conceptual understanding and complex-skill development, especially when learners receive appropriate scaffolding and opportunities for reflection. PhET's research-informed design process begins with learning goals and uses iterative student interviews and classroom study. Its teaching guidance also emphasises autonomy, guided inquiry and teacher facilitation rather than prescriptive click-by-click worksheets.
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Selected evidence
- Chernikova, O., et al. (2020). Simulation-based learning in higher education: A meta-analysis. Review of Educational Research, 90(4), 499–541.
- PhET Interactive Simulations. Research and Design.
- PhET Interactive Simulations. Facilitating PhET Simulation Use.
- McKagan, S. B., et al. (2008). Developing and researching PhET simulations for teaching quantum mechanics. American Journal of Physics, 76, 406–417.
Last reviewed: 25 July 2026
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