Year: 2025
Type: article
Study design: Clinical Trial
Abstract: This study explores the efficacy of Augmented Reality (AR) and Artificial Intelligence (AI) comics as an advent educational tool to enhance students' understanding of fiqh almuamalat (Islamic Commercial Jurisprudence).The SmartMuamalatAI project was developed to rectify concerns of low motivation and limited student comprehension that is due to the consequence of traditional Islamic finance knowledge.This was bridged through the revision of complex Shariah principles towards compelling and accessible educational content.Using a quantitative pre-and post-test design with 98 students, AR-enhanced comic modules with AI-driven explanatory videos, interactive images, and realistic Islamic finance cases were developed that comprised of surveys which measures understanding, perception, and cognitive effort based on the three Course Learning Outcomes (CLOs): conceptual understanding, implementation of Shariah solutions, and contextualisation within realistic cases.The findings recommend strategic improvements across all CLOs.From the findings, the students' confidence in explaining concepts improved significantly (mean score has increased from 4.23 to 4.40).Moreover, the readiness to include Shariah-friendly options has slightly increased from 4.35 to 4.58.However, the students felt that they only exert a small amount of mental effort.Also, stress levels are staying low or medium and decreasing slightly from 71% to 69%.This means that the students were actively engaged but not too overwhelmed.The students' understanding of the core ideas like gharar, riba, and valid contracts have also slightly improved given the feedback scores.This is true especially since post-learning averages amassed over an average of 4.5.The findings suggests that AR and AIenabled comics helped enhance understanding, interest, and thinking prowess when studying Islamic finance.Instead of only theoretical, SmartMuamalatAI proves that the
Institution: Sultan Zainal Abidin University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W4416104254