Neural network modeling for an intelligent recommendation system supporting SRM for universities in Thailand

In order to support the academic management processes, many universities in Thailand have developed innovative information systems and services with an aim to enhance efficiency and student relationship. Some of these initiatives are in the form of a Student Recommendation System (SRM). However, the success or appropriateness of such system depends on the expertise and knowledge of the counselor. This paper describes the development of a proposed Intelligent Recommendation System (IRS) framework and experimental results. The proposed system is based on an investigation of the possible correlations between the students' historic records and final results. Neural Network techniques have been used with an aim to find the structures and relationships within the data, and the final Grade Point Averages of freshmen in a number of courses are the subjects of interest. This information will help the counselors in recommending the appropriate courses for students thereby increasing their chances of success