Development of an education recommender system

Abstract

In a world where knowledge, distance and cultures coalesce into a unified amalgam, technology arises as a pioneering language that promises to bridge all gaps and foster a smoother intermixing. While technology serves as a tool for facilitating this, the real essence of holistic development lies in equipping ourselves with knowledge, and indulging in a continuous process of learning. With the rapid advancements in technology that we see around us today, access to educational resources has become easier than ever before.

When technology is coupled with traditional teaching methods, its efficiency is increased manifold, as is evident from the widespread use of e-learning portals. Education recommender systems must ideally identify the necessities and best interests of the students and professors and cater to them efficiently. Availability of high-rated learning material, related research journals, demonstrations of practical learning experiments, periodic assessments and applying performance based evaluation to position students’ caliber among their peers are some of the sought after features in a good educational recommender system.

A centralized system incorporating all these features would also help students who are performing below par to be guided by their mentors with further academic recommendations so that they may benefit from an enhanced learning experience.

In this report, the author discusses some research work done in the area of developing educational recommendation algorithms. The author also discusses the architecture of a recommender system that has been built to serve the above- mentioned purpose and highlights the functionalities involved in the implementation of iEDUcateU, the proposed system. The relevance of the proposed system, recommendations for future work and an elaborate summary are provided in later sections of this report.