An institution recommender system based on student context and educational institution in a mobile environment

In this day and age, many universities in Thailand have specific targets for students to achieve academic success and earn honours degrees. Such targets are based in part on the unique identity of each university. This paper aimed to provide a modelling and recommender application, which gathers and utilises the characteristics and attitudes of students in order to accurately predict and select the most appropriate learning institution for particular students through data analytics techniques. The system consisted of three main processes to recommend students for the appropriate university, including design tools, development tools, and analytical tools. The data for the instant research was gathered from 1,109 students at three universities, including Rajabhat Mahasarakham University, Mahasarakham University, and the University of Phayao. The methods used to formulate suggestions were decision tree and association rule. The results indicated that accuracy was significant for four factors in the application, including the popularity of the universities, trust in the institutions, the skills of learners, and family income. The constructed model had 69.03 % accuracy, supporting the proposition that the model revealed a reasonable relationship between students and appropriate universities when utilising this decision-support system.