Canva-Based Moral Education Media Integration and Deep Learning Approach in Strengthening the Learning Climate in Elementary Schools

Abstract

This research aims to develop a conceptual model of the integration of Canva-based moral education media and an in-depth learning approach in strengthening the learning climate in elementary schools. The research uses a qualitative approach of the type of library research which is presented in the form of a conceptual study. Data is sourced from articles from accredited national journals and reputable international journals published in 2015–2025, as well as theoretical literature related to character education, digital media, deep learning, and learning climate. The analysis is carried out through descriptive-analytical techniques and content analysis to identify core concepts, examine the theoretical relationships between variables, and formulate an integrative framework. The synthesis results show that Canva functions as a visual-reflective medium that concretizes moral values through experiential digital projects, while the deep learning approach encourages exploration, reflection, and personal meaning of value. A supportive learning climate acts as a psychosocial context that mediates student engagement and internalization of values. The integration of these three components forms a conceptual model that connects digital media, reflective pedagogical strategies, and classroom climate in support of sustainable character building. Theoretically, this study expands the theory of multimedia learning and meaningful learning within the framework of value-based moral education and provides a foundation for further empirical research. Thus, Canva's integration and deep learning within the framework of the learning climate provides a relevant conceptual model for strengthening moral education in primary schools.