Generative AI-Assisted Living Qur’an And Hadith Learning To Enhance Students’ Higher Order Thinking Skills - Devi Faizah Yuliana; Juli Sardi (Lembaga Riset dan Inovasi Almatani, 2026)
This research was motivated by the dominance of textual and teacher-centered learning approaches in Islamic education, which have not optimally developed students’ higher-order thinking abilities. In addition, studies on the integration of Generative AI in Islamic learning, particularly in Living Qur’an and Hadith courses, remain limited. This study aims to analyze the effect of Generative AI-assisted learning of the Living Qur’an and Hadith on students’ Higher Order Thinking Skills (HOTS) in Islamic higher education. This study employed a quantitative quasi-experimental pretest-posttest control group design. The participants consisted of 33 students, divided into an experimental group of 18 and a control group of 15. The experimental group participated in Generative AI-assisted learning of the Living Qur’an and Hadith, while the control group received conventional instruction. The research instrument was an HOTS essay test covering the skills of analyzing, evaluating, and creating. Data analysis was conducted using descriptive statistics, normality and homogeneity tests, an independent-samples t-test, and effect size analysis. The results showed that Generative AI-assisted learning of the Living Qur’an and Hadith had a positive and significant effect on students’ HOTS, with a significance level of 0.001 < 0.05. The experimental group obtained a posttest mean score of 78.44, which was higher than the control group’s score of 70.13. Furthermore, the effect size analysis showed a Cohen’s d value of 1.25, categorized as a large effect. The findings indicate that integrating Generative AI supports more reflective, contextual, and student-centered learning, thereby contributing to the development of students’ higher-order thinking skills in Islamic higher education.