Exploring the Impact of Financial Stress on Students’ Academic Performance: A Machine Learning Approach

Student stress is a significant phenomenon that has an impact on students’ performance and achievement, and affects many students worldwide. Financial challenges in college. Students can cause both mental health issues and poor academic performance. A research study of 2,902 college students aim is to examine how factors and opinions influence the amount of financial stress faced by students and its relationship to academic success. Research focus on a model to identify financial stress in pupils. The research plan is based on physical and cognitive activities that students engage in, such as studying, sleeping, or using a mobile device, and having their wrist sensors measure their pulse rates. In order to create the model, we are running a study to collect data from college students. Machine learning techniques are the foundation of our proposal. J48, random forests (RF),Naive Bayes, and KNN were used to build the prediction models and parameters of the confusion matrix were used to assess each prediction model’s performance. The model performed well in our evaluation, yielding accuracy of $85 \%$ on training data, $82 \%$ in testing data.