Evaluating the Effects of Personalised Learning on AI‐Assisted Design Performance, Creative Self‐Efficacy, and Engagement of High‐ and Low‐Performing College Design Students.

Background: In recent years, the integration of large language models has brought significant opportunities for advancing personalised learning in higher education. However, little attention has been paid to how students of different performance levels benefit from such tools, especially in creative...

Descripción completa

Detalles Bibliográficos
Publicado en:Journal of Computer Assisted Learning Vol. 42; no. 2; pp. 1 - 22
Autores principales: Wang, Jiawei, Zhang, Jingru, Kang, Yuan
Formato: pictorial research tables/charts randomized controlled trial Journal Article
Publicado: Wiley-Blackwell Apr2026
Acceso en línea:Ver este registro en EBSCOhost