Taking a major leap towards revolutionizing the education sector, scientists at Nagaland University have come up with an Artificial Intelligence (AI)-based system with an objective of providing customized learning experience for students in colleges and universities. The system, called the ‘Flexible Learning System’ (FLS), is intended to provide learning material customized to the specific level of comprehension and performance of each student, which is a major leap in digital and adaptive learning processes.

The FLS is constructed upon the foundation of Intelligent Tutoring Systems (ITS), which are AI-powered learning platforms that adapt teaching content according to unique learner profiles. What distinguishes the FLS is that it incorporates Multi-Access Edge Computing (MEC) — an advanced addition to cloud computing that loads applications near to the end user. With this capability, real-time responsiveness is achieved, dramatically improving learning by making it more efficient and responsive.

Designed at the School of Engineering and Technology, Nagaland University, the FLS is meant to fill the gaps that currently exist in conventional ITS tools, more specifically when it comes to real-time responsiveness. The researchers say that existing ITS models lack when it comes to generating dynamic learning trajectories that can adjust in real time to a learner’s strengths and areas of weakness. The new system settles this issue through the use of MEC to present content in relation to unique learning patterns and performance levels.

FLS sorts course materials into three difficulty levels — easy, moderate, and advanced — such that all the students navigate a learning stream relevant to their class aptitude. This benefits the students to acquire knowledge individually while assisting instructors to know exactly where students need assistance. Adaptive capability evaluates students continuously on an answer-by-answer basis and alters content difficulty subsequently accordingly.

The research team, whose leaders are Assistant Professors Ramesh Singh, Chenlep Yakha Konyak, and Akangjungshi Longkumer of the Department of Computer Science and Engineering, presented remarkable outcomes in their research. They showed that the FLS lowered the time to process tasks by 94%, an imposing increase which results in quicker feedback, more engagement, and more customized guidance. Although the study now points to the development of the system and its feasibility at a technical level, the group has recommended more testing in order to assess its practical application within wider learning settings.

Vice-Chancellor of Nagaland University Prof Jagadish K Patnaik welcomed the move, saying the FLS would not only enable students to pass by giving them suitably challenging material but also lead those struggling academically. He pointed to the system’s potential to direct education in the future via advanced technologies like the Internet of Things (IoT), Augmented Reality (AR), and Virtual Reality (VR). These technologies, when combined, could provide engaging and immersive learning spaces while having ultra-low power usage to enable sustainable and inclusive education.

Speaking of the impetus for the research, Chenlep Yakha Konyak noted that with the increase in ITS adoption, the lack of real-time adaptability still poses a major impediment to providing truly personalised learning. The FLS, he continued, addresses this imbalance by allowing constant interaction between the learner and the system, which leads to an improved learning experience.

In continuation of explaining the system’s effectiveness, Ramesh Singh mentioned that employing MEC architecture enables the platform to optimize bandwidth as well as processing capability. This way, even institutions with limited digital infrastructure can avail themselves of the power of the system. He emphasized that the platform’s auto-content categorization and user interaction capabilities facilitate smoother student-instructor communications.

As per Akangjungshi Longkumer, effective deployment of FLS can transform teaching methodologies by providing personalized learning paths for students. The scalability of the system also makes it a prime candidate for large-scale adoption by education institutions. He opines that such adaptive systems based on AI can enhance not just academic performance but also motivation and engagement of students.

The research findings were published in the peer-reviewed International Journal of Information Technology (DOI link), further confirming its scholarly and pragmatic significance.

With growing focus on online learning, Nagaland University’s AI initiative provides a strong model for how institutions can leverage new technologies to address the varied and changing needs of students. As education becomes more personalised and inclusive, such innovations could soon become the foundation of academic achievement in the digital era.