Nagaland University researchers develop AI-driven flexible learning system for enhanced education
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Researchers at Nagaland University have designed an innovative Flexible Learning System (FLS) aimed at revolutionising personalised education through the application of Multi-Access Edge Computing (MEC).
This advanced system facilitates real-time, adaptive learning experiences, enabling students to learn at their own pace with customised content tailored to their abilities and progress.
The research, conducted at the School of Engineering & Technology, demonstrated that FLS can reduce task processing time by an impressive 94%, significantly boosting efficiency and responsiveness in learning environments. By categorising students based on their performance levels - easy, moderate, or advanced - the system ensures that learning materials are appropriately tailored, addressing weak areas and enhancing overall comprehension.
Led by researchers Ramesh Singh, Chenlep Yakha Konyak, and Akangjungshi Longkumer from the Department of Computer Science and Engineering, the study was recently published in the renowned International Journal of Information Technology.
The team noted that FLS addresses a critical shortcoming in traditional Intelligent Tutoring Systems (ITS) by providing real-time adaptive learning capabilities. Unlike conventional ITS tools, FLS leverages MEC technology to optimise bandwidth usage and streamline task processing, ensuring seamless interactions between students and instructors.
Highlighting the future potential of this system, Nagaland University Vice-Chancellor Prof. Jagadish K. Patnaik praised the innovation, pointing out that future iterations of FLS will incorporate Internet of Things (IoT) technology for deeper insights into learning patterns. Additionally, the integration of Augmented Reality (AR) and Virtual Reality (VR) is expected to enhance interactivity and engagement, especially in areas with limited infrastructure.
The system will also provide instructors with instant access to student progress data, making educational oversight more efficient.
Assistant Professor Chenlep Yakha Konyak stated that while the framework is still under development, further testing and commercialisation efforts are planned. “This system has the potential to be widely adopted by educational institutions, providing real-time, tailored learning experiences that improve student engagement and outcomes,” Konyak remarked.