Causal Direction between Design Thinking Practices and Mathematical Modelling Self‑Efficacy in AI‑Supported Learning

Determine whether cultivating specific design thinking practices—particularly feedback seeking, experimentalism, and collaboration—directly enhances students’ mathematical modelling self‑efficacy within AI‑supported learning environments, and ascertain the causal direction of the observed relationships between these design thinking dimensions and mathematical modelling self‑efficacy.

Background

The study used correlational analyses and PLS‑SEM to show that design thinking and computational thinking positively predict mathematical modelling self‑efficacy, with collaboration, experimentalism, and feedback seeking exhibiting the strongest links. Because the design is cross‑sectional and observational, causality cannot be inferred.

The authors explicitly note that they cannot determine the causal direction of the association between design thinking practices and mathematical modelling self‑efficacy. They propose longitudinal and intervention‑based studies to evaluate whether cultivating design thinking practices (e.g., question‑asking and experimentation) produces direct improvements in self‑efficacy during AI‑supported mathematical modelling.