Examining the effect of the computational models on learning performance, scientific reasoning, epistemic beliefs and argumentation: An implication for the STEM agenda

Simulation-based learning enables structured 'what-if' exploration and interpretation of outputs, but its learning value depends on whether assessment prompts require students to articulate governing principles and justify decisions rather than only operating the tool.

“In classroom settings, SBL enables structured ‘what-if’ exploration and interpretation of outputs (e.g., trend plots and computed variables), but its learning value depends on whether assessment prompts require students to articulate governing principles and justify decisions rather than only operating the tool [21].”

Simulation-supported learning presents a risk that students may rely on simulator outputs without sufficiently articulating the governing principles, assumptions, and causal mechanisms underlying those outputs.

“However, simulation-supported learning also presents a well-recognized risk: students may rely on simulator outputs without sufficiently articulating the governing principles, assumptions, and causal mechanisms underlying those outputs.”