My Research
My research journey encompasses both PhD and Master by Research studies, focusing on educational technology, mobile learning frameworks, and MOOC performance measurement models.
PhD Research Study
MPM Model: Cross-Platform MOOC Performance Measurement Model
The MPM (MOOC Performance Measurement) Model is a comprehensive framework designed to measure course and learner performance across cross-platform Massive Open Online Course (MOOC) environments. The model introduces Consideration Factor indicators across five key performance areas, providing actionable insights for continuous improvement. Currently tested and validated on FutureLearn and OpenLearning MOOC platforms, the MPM Model offers institutions a robust methodology for understanding and optimizing MOOC effectiveness.
Master by Research Study
MMCD Framework & Methodology: Multimedia Mobile Content Development Framework
The MMCD (Multimedia Mobile Content Development) Framework and Methodology provides a systematic approach for developing robust mobile learning (m-learning) applications. The framework encompasses five core development stages: (1) application idea creation, (2) structure analysis, (3) process design, (4) main function development, and (5) testing. The MMCD component architecture manages navigation, content management, application logic, and database operations, enabling developers to accelerate development while ensuring consistent application performance. This framework has been successfully applied in multiple m-learning projects and published in peer-reviewed journals.
Interactive Hologram Research Group (iHO)
Interactive Hologram for Medical Diagnosis & Healthcare Innovation
Interactive Hologram Research Group
The Interactive Hologram (iHO) is a special interest research group based at the Faculty of Information & Communication Technology (FTMK), UTeM, focused on leveraging holographic technology and artificial intelligence for medical education and healthcare delivery. The research initiative encompasses two main phases: (1) design and development of an interactive hologram system for eye retina diagnosis learning, enabling medical students and professionals to understand retinal pathology through immersive visualization, and (2) development of an AI and machine learning-based diabetic retinopathy diagnosis system utilizing advanced image processing techniques for automated detection and classification of retinal abnormalities, integrated with appointment management functionality. The latter phase was developed under postgraduate supervision and collaboration with Hospital Besar Melaka, providing ophthalmologists with a comprehensive AI-assisted diagnostic and scheduling tool for patient management.
Key Research Components:
- Interactive Hologram Technology: Design and development of immersive holographic visualization for eye retina anatomy and pathology learning
- AI & Machine Learning Image Processing: Advanced image processing algorithms and deep learning models for automated detection, segmentation, and classification of retinal pathologies including diabetic retinopathy stages
- Diabetic Retinopathy Diagnosis System: AI-assisted diagnostic platform leveraging computer vision and machine learning for detecting and classifying diabetic retinopathy severity stages from fundus images
- Clinical Appointment System: Integrated scheduling and management system for Hospital Besar Melaka ophthalmology department with AI diagnosis integration
- Postgraduate Research Supervision: Guided development of the diagnosis system with focus on clinical validation, real-world healthcare integration, and machine learning model optimization
Research Publications & Outputs
MPM Model - MOOC Performance Analysis
Comprehensive analysis and validation of the MOOC Performance Measurement Model across multiple online learning platforms.
Access Publication →MMCD Framework - Mobile Learning Development
Systematic framework for mobile learning application development with focus on content management, navigation, and database architecture.
Read Publication →Interactive Hologram (iHO) - Medical Diagnosis Research
Research on holographic visualization for medical education and development of AI and machine learning-based diabetic retinopathy diagnosis system utilizing advanced image processing for retinal image analysis and detection, with clinical integration at Hospital Besar Melaka.
View Research Details →Educational Technology & Learning Analytics
Ongoing research in the intersection of educational technology, data-driven learning insights, and MOOC platform optimization.
Inquire →Research Expertise & Specializations
MOOC Performance Measurement
Expert in designing and implementing performance measurement models for Massive Open Online Courses, with focus on learner success metrics and platform optimization across FutureLearn and OpenLearning environments.
Mobile Learning Framework Design
Specialized in developing comprehensive frameworks for mobile learning application development, including architecture design, content management systems, and methodological approaches.
Healthcare Technology & Medical AI
Expertise in designing holographic visualization systems for medical education and developing AI/machine learning-based diagnostic platforms with focus on image processing for retinal pathology detection and classification, including clinical validation and collaboration with medical institutions.
Postgraduate Research Supervision
Experienced in guiding postgraduate students through complex research projects from conception to clinical validation, with emphasis on translating research into practical healthcare solutions and real-world deployment.
Educational Technology Innovation
Passionate about leveraging technology to improve educational and healthcare outcomes through systematic research, data-driven insights, and innovative solutions.