Artificial Intelligence in Islamic Religious Education: Enhancing Critical Thinking through AI Feedforward Feedback Models - Maralottung Siregar; Khatami Ayu Rini; Siti Halimah; Mohamed Lahby (Jurnal Pendidikan Progresif, 2026)
Integrating the AI Feedforward Feedback (AI-FF) Model into Islamic Religious Education to Enhance Students’ Critical Thinking Skills. This study aims to analyze the effectiveness of the AI-FF model in enhancing the critical thinking skills of Islamic Religious Education students, explore students' and lecturers' experiences during implementation, and evaluate the extent to which AI integration can be applied without diminishing teachers’ moral and spiritual roles. A mixed-method approach was employed. Quantitative data were gathered through a quasi-experimental pretest–posttest design, while qualitative data were collected through in-depth interviews and structured observations. Statistical analyses were used to determine the model’s effectiveness, and thematic analysis was applied to interpret learning experiences. The findings demonstrate that AI-FF effectively improves students’ critical thinking skills, especially in analysis, argument evaluation, and metacognitive reflection. Qualitative results indicate that AI-FF provides cognitive scaffolding without replacing the teacher’s moral guidance. Students reported improved confidence and more structured reasoning, while lecturers perceived AI as an augmentative tool. AI-FF can be ethically integrated into Islamic Religious Education when positioned as a supportive tool that strengthens cognitive processes while preserving the teacher’s authority in moral and spiritual guidance. The study highlights the need for educators to develop AI ethics literacy and for integration models that maintain teacher primacy while leveraging AI as a cognitive facilitator. Keywords: AI feedforward feedback, critical thinking, islamic religious education, AI ethics, technology-enhanced learning.