Deep Learning in Technology Enhanced Project Based Learning for Art and Cultural Creative Education Using PLS SEM and IPMA

Abstract

This study explores the fundamental mechanisms through which technology-enhanced project-based learning (TE-PjBL) facilitates deep learning (DL) within the domain of art and cultural creative education. Building on Sociocultural Theory, the research constructs and empirically verifies a theoretical model that connects learning resources (LR) and organizational management (OM) to DL via student-student interaction (SS), student-teacher interaction (ST), and teacher scaffolding (SF). Data collected from 224 undergraduate participants were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and Importance-Performance Map Analysis (IPMA). The findings demonstrate that knowledge transfer (KT) serves as a central predictor of DL, with SS and SF making significant contributions to KT. In contrast, ST exhibits a negative association with KT, indicating that excessive instructor involvement may constrain students’ capacity for self-directed learning. LR and OM show strong positive impacts on SS, SF, and ST, further affirming their importance in fostering structured and interactive learning environments. IPMA results also highlight KT, SS, and SF as key areas warranting strategic emphasis. These findings emphasize the necessity of integrating guided instructional support with opportunities for learner autonomy, as well as leveraging digital resources strategically to enhance collaborative and creative engagement in art-oriented educational contexts.