Volume I: Eco-Theology, Spirituality, and Environmental Ethics

AI-Driven Adaptive Learning in Islamic Higher Education: Enhancing Students’ Theological Reasoning and Eco-Theological Literacy

  • Ahmad Fauzi Zakaria UIN Sunan Gunung Djati Bandung, Indonesia

Keywords

Adaptive Learning; Artificial Intelligence; RAG system; theological critical thinking; eco-theology.

Abstract

This study aims to develop and analyze the conceptual framework of an AI-based adaptive learning model utilizing a Retrieval-Augmented Generation (RAG) system to enhance both digital religious literacy and theological reasoning, specifically focusing on integrating eco-theological concepts among Islamic Education (PAI) students. Employing a Research and Development (R&D) approach aligned with the ADDIE model, this research is grounded in a techno-pedagogical and qualitative framework. A preliminary needs analysis was conducted via a diagnostic survey involving 31 PAI students at Institut KH Ahmad Sanusi Sukabumi. The findings indicate a severe epistemic vulnerability within contemporary digital spaces, where 87.10% of students frequently encountered "AI hallucinations" or fabricated religious data generated by public commercial AI tools. Concurrently, an overwhelming 87.10% of respondents strongly demanded an authoritative, isolated, and structured AI learning ecosystem to prevent religious reference disorientation. In response to these empirical field realities, a customized Web-LMS prototype featuring smart routing capabilities was engineered, locking its vector database exclusively to verified Islamic texts, classical turats, and specialized eco-theology modules. Ultimately, this article contributes to the discourse on modernist Islamic pedagogy by successfully harmonizing rational reasoning (Aqli) and textual authenticity (Naqli), thereby cultivating a "Digital Burhani" epistemic framework among students to anchor cultural and ecological resilience in the multipolar era.

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