Custom GPT MQA Advisor for academic accreditation: innovation at the Kulliyyah of Medicine

• Main Authors: Wan Salleh, Wan Muhamad Salahudin, Abd. Rahim, Nour El Huda
• Format: Article
• Language: English; English; English; English; English; English
• Published: Kulliyyah of Allied Health Sciences, International Islamic University Malaysia 2024
• Subjects: AI Indexes (General); R Medicine (General)
• Online Access: http://irep.iium.edu.my/113204/47/113204_Custom%20GPT%20MQA%20Advisor%20for%20Academic%20Accreditation%20Innovation%20at%20the%20Kulliyyah%20of%20Medicine.pdf; http://irep.iium.edu.my/113204/18/113204_CustomGPT%20MQA%20advisor%20for%20academic%20accreditation_programme%20book.pdf; http://irep.iium.edu.my/113204/19/113204_CustomGPT%20MQA%20advisor%20for%20academic%20accreditation_certificate.pdf; http://irep.iium.edu.my/113204/20/113204_CustomGPT%20MQA%20advisor%20for%20academic%20accreditation_poster.pdf; http://irep.iium.edu.my/113204/35/Abstract%20IJAHS.pdf; http://irep.iium.edu.my/113204/36/Programme%20Book.pdf; http://irep.iium.edu.my/113204/; https://journals.iium.edu.my/ijahs/index.php/IJAHS
• Institution: Universiti Islam Antarabangsa Malaysia

The CustomGPT MQA Advisor represents a significant leap in research-based innovation, integrating cutting-edge AI technology to address the complexities of the Malaysia Qualifications Agency (MQA) standards and Malaysia Medical Council (MMC) requirements in Kulliyyah of Medicine. This digital advisory system exemplifies the fusion of advanced natural language processing (NLP) and bespoke software engineering, providing higher education institutions with precise, real-time guidance on accreditation requirements. Developed using the GPT-4 framework, the advisor is capable of processing and understanding extensive MQA and MMC documentation with exceptional accuracy and nuance. It offers users an interactive platform where inquiries can be addressed contextually, akin to conversing with a human expert. The system's ability to reference specific sections of official documents bridges the gap between complex policy language and practical application, streamlining the accreditation process and enhancing users' comprehension of accreditation guidelines. Furthermore, the advisor's stateful memory system ensures continuity in interactions, tailoring advice based on the institution's history and needs. Its user-friendly interface presents feedback clearly and concisely, making it accessible to all stakeholders regardless of their familiarity with accreditation policies. As MQA and MMC update their standards, the advisor continuously learns and assimilates new information, providing institutions with the most current and relevant guidance. This ongoing evolution ensures that educational institutions remain compliant and prepared for successful accreditation, ultimately elevating the quality of education through informed decision-making.