Simulation — the use of modeled environments, agents, or scenarios to support learning through practice and feedback in contexts that are safe, repeatable, and often otherwise inaccessible. Simulations let learners act, make errors, and see consequences without real-world cost, and are increasingly powered by AI and agent-based modeling.
Simulation sits at the core of experiential and Active Learning pedagogies. It provides the deliberate practice, productive failure, and feedback loops that build skill and judgment. AI has transformed simulation in two ways: it powers more realistic and adaptive simulated environments, and it generates simulated learners, patients, or interlocutors that make practice scalable.
AI and simulation
AI-powered environments: adaptive simulations adjust difficulty and scenarios to a learner's state, linking to Adaptive Learning and Reinforcement Learning-based coaching.Simulated agents: AI can simulate patients (for medical training), students (for teacher practice), or conversation partners, making high-stakes interpersonal practice accessible and repeatable.Simulated learners: models of student behavior let researchers and designers test tutoring systems and curriculum before live deployment, grounding Student Modeling and Knowledge Tracing.Trust and fidelity: the value of a simulation depends on how faithfully it models the real context — and on the learner's awareness of its limits, connecting to Trust Calibration.Connections
Simulation connects to Active Learning, Adaptive Learning, and Pedagogical Agent. It is a mechanism for experiential and Constructivist learning and is amplified by AI's ability to generate adaptive, realistic practice environments.
Connected Concepts
Active LearningAdaptive LearningPedagogical AgentReinforcement LearningStudent ModelingConstructivistTrust CalibrationProfessional TrainingConnected Articles
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