Impact of 6C Integrated Deep Learning on Pre-service Elementary Teachers' Social Studies Understanding

Abstract

Digital education transformation requires pre-service elementary teachers to possess solid pedagogical foundations and deep conceptual mastery. This study evaluates the effectiveness of a 6C-integrated Deep Learning model in enhancing pre-service elementary teachers' understanding of the Basic Concepts of Social Studies. Using a quantitative quasi-experimental, single-group Time Series Design, 39 pre-service elementary teachers (N = 39) were assessed through repeated conceptual understanding tests and Student Worksheets for Learning (LKM) applying meaningful, mindful, and joyful principles. Data were analyzed using Repeated Measures ANOVA, supplemented by Rasch model calibration, descriptive statistics, and Spearman's rank correlation. The 6C-integrated Deep Learning model significantly improved students' conceptual understanding (F = 23.930; p < .001), with empirical LKM data confirming this trend through an average score increase from 65.26 to 91.85. Critical Thinking emerged as the highest-scoring 6C indicator on the Likert scale (M = 3.17). These findings suggest that integrating Deep Learning with the 6C framework can enhance pre-service elementary teachers' conceptual understanding, promote higher-order learning competencies, and support teacher education through more reflective and adaptive learning experiences