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Software developers can borrow a useful set of principles from research on children’s learning: build on what learners already know, give them meaningful things to do, provide timely support, and increase challenge as they become more capable. The lesson is not to make every app playful or leave users to explore on their own. Engagement is not proof of learning, and the right design depends on what users should understand or be able to do.
Start with what learners already know
Children do not arrive as blank slates. They bring ideas, skills, and ways of interpreting the world that instruction can build on. The National Research Council made this point in Taking Science to School, a 2007 report on science education.
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For developers, the practical equivalent is to learn how users understand a task before deciding what the interface should teach them. Watch people try the product, listen to how they describe what they see, and note where their mental model differs from the system’s. A tutorial that assumes users know nothing can waste time; one that assumes too much can leave them stranded.
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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallThere is no universally best instructional format. As the National Research Council’s chapter emphasizes, the useful question is “better for what?” A design that helps someone remember a sequence may not help them explain a concept or transfer a skill to a new situation.
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Make exploration purposeful
Letting learners click around is not, by itself, a learning strategy. Inquiry can be valuable when users have a meaningful question or task, can observe the consequences of their choices, and receive help noticing what matters. Without that structure, they may get stuck or focus on irrelevant details.
The National Research Council cautions that “Simple experience with inquiry alone does not lead to acquisition of better experimentation skills or conceptual mastery.” For software, this means pairing user agency with a purpose: pose a problem, make relevant outcomes visible, and help users connect their actions to evidence.
A 2019 OECD discussion of experimental-design tutors described digital activities that walked learners through projects but often did not help them design experiments or receive feedback on their designs. That dated example illustrates a broader design risk: completing steps is not the same as learning the underlying process.
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Use scaffolding to help users do more
Scaffolding is support that enables a learner to do more sophisticated work than they could manage without it. It can come from another person, a physical material, or software. In an interface, scaffolding might focus attention on a relevant feature, show a relationship between variables, or prompt a user to explain what their observations suggest.
Good support helps users think; it does not merely announce whether they are right or wrong. A hint can point toward the next useful observation while leaving the learner responsible for making sense of it. Support should also fit the task: an early explanation may be useful when a concept is new, while a later task may call for less direction.
Increase challenge as learners gain skill
A study by Melissa N. Callaghan, published online in 2020 and in a 2021 journal volume, tested an app with 240 children aged 4–5 learning novel words. Scaffolded verbal hints were especially useful early in app play. Children also responded faster and more accurately when challenge increased gradually than when challenges appeared in random order.
This is evidence from one preschool learning-app study, not a guarantee that every product should use the same progression. Developers should test whether gradual challenge helps with their audience and target skill. A useful sequence gives learners a chance to establish a foothold before asking them to handle more difficult work.
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Choice can help learners feel involved, but unrestricted choice may make it hard to know what to do or what to notice. The National Research Council’s 2011 review of games and simulations describes this tension: some autonomy may motivate learners, while open-ended inquiry can confuse them. A combination of guidance and meaningful control may work better, depending on the intended outcome.
When evaluating a learning experience, consider how these design dimensions fit together:
- Outcome: Is the goal conceptual understanding, a process skill, motivation, or transfer to a new context?
- Guidance: What support is needed, and when should it appear?
- Control: Which decisions can learners make without losing the thread of the task?
- Challenge: Does difficulty build in a way that suits the learner and the skill?
- Prior knowledge: Might different users need different explanations, representations, or pacing?
Measure learning, not just engagement
A product can hold attention without producing durable understanding. The National Research Council’s 2011 report found promising evidence that simulations can enhance conceptual understanding, while describing the evidence for games as limited and inconclusive. It also stressed that effective science simulations require good design, testing, and appropriate scaffolding.
Those findings do not establish that a particular game or simulation works, nor that results transfer across subjects and users. The report identified gaps in controls, context, and generalizability; the 2007 National Research Council chapter likewise noted that much evidence came from small-scale, long-term intervention studies and did not establish a single best design or strong results at scale.
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Make social support relevant
People who learn with children can influence the experience, but interaction is not automatically helpful in every form. A 2019 study of ScratchJr found that task-relevant parent-child interaction predicted coding learning, while question-asking was a negative predictor in that particular study. This does not mean questions are generally harmful; it is a reminder to test how prompts work in context rather than assuming that more interaction is always better.
Apply the principles with care
The evidence behind these ideas is weighted toward science inquiry, simulations, preschool apps, and early coding. It does not establish that the same interventions work equally well for every age, subject, culture, or product. Treat the principles as hypotheses for design, then evaluate them with the learners and outcomes your software is meant to serve.
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