Decision-making is one of the key activities that humans participate in. As a person develops, so does their decision-making preferences. Since choosing a major is often undergone at a young age, peop..
Decision-making is one of the key activities that humans participate in. As a person develops, so does their decision-making preferences. Since choosing a major is often undergone at a young age, people often decide to switch for a more suitable major based on their current preferences. Given that major switching is common in STEM fields, and STEM’s growing importance in the modern landscape, this study aims to investigate determinants of major switching in undergraduate students. Based on our initial results, deep learning produced the best AUC, precision and recall compared to other algorithms. The confusion matrix implies that the algorithm is effective at predicting if a student will switch majors. Top correlation factors found for major switching were age, ACT scores, and GPA. Results from this study can be used to detect and predict students most likely to switch majors.
