Implementing an individualized recommendation system using latent semantic analysis

Abstract

In this paper, a novel recommendation system for students and instructors is introduced utilizing a natural language processing system called Latent Semantic Analysis. This recommendation system allows students to get immediate help via recommendations for further studying which may otherwise cause students to get stuck and not progress further until the next lecture or meeting with an instructor or teaching assistant. This same system can also provide student profiles for instructors to review before meeting with a student. The implementation of system is aimed toward streamlining the process of receiving help, saving time for both students and instructors while encouraging deeper conceptual discussion with the remaining and saved time.