Enhancing Social Studies Learning Achievement and Analytical Thinking through the Historical Method Integrated with Artificial Intelligence

Abstract

Developing students’ analytical thinking and disciplinary understanding in social studies is essential for preparing them to engage with historical information critically, and integrating the historical method with artificial intelligence offers a promising approach to support these goals. Therefore, the purposes of this study were to: (1) develop an instructional model using the historical method integrated with AI to meet the 80/80 efficiency criterion, (2) compare students’ learning achievement before and after the intervention, and (3) compare their analytical thinking performance across the same phases. The participants were 35 Grade 12 students selected through cluster random sampling. The instruments included four learning management plans, a 20-item learning achievement test, and a 20-item analytical thinking test. Data were analyzed using descriptive statistics, E1/E2 efficiency analysis, and dependent samples t-tests. The results showed that the instructional model achieved E1/E2 values of 84.65/83.18, exceeding the 80/80 benchmark, and that students’ posttest scores in both learning achievement and analytical thinking were significantly higher than their pretest scores. These findings contribute to the literature by demonstrating the potential of AI-supported historical inquiry to enhance cognitive outcomes in social studies education.