The process of choosing a suitable university program can be overwhelming for first-year students. To address this challenge, we have developed Betr Selektr, a comprehensive program recommender system that takes into account the student's personality type and academic results. The system employs the Myers-Briggs Type Indicator (MBTI) framework to determine the personality type of the student and combines it with their high school results to generate a personalized index figure – a personality type. This personality type is used to recommend degree programs that align with the student's interests, strengths, and academic background. The system is built using the waterfall development methodology, incorporating tools such as Visual Studio Code for development, SQLAlchemy for database management, Flask for web application development, and SQLite for data storage. The project encompasses various stages, including systems analysis and design, implementation and testing, and the utilisation of research methodologies. Through this project, we aim to assist first-year students in making informed decisions about their university programs by providing personalized recommendations based on their unique profiles. Betr Selektr offers a user-friendly interface, efficient data processing, and accurate program recommendations, making it a valuable tool in the university application process.

Authors:
Belinda Mutunhu Ndlovu, Unisa, South Africa
Zirah Migioni, National University of Science and Technology, Zimbabwe
Sibusisiwe Dube, National University of Science and Technology, Zimbabwe
Phillip Nyoni, National University of Science and Technology, Zimbabwe

About the Presenter(s)
Ms Belinda Mutunhu Ndlovu is a University Doctoral Student at UNISA in South Africa

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