Abstract: College students are suffering from many mental health problems including mental stress, somatization, obsession, interpersonal sensitivity, depression, anxiety, hostility, fear, paranoia, and psychosis, which can bring a lot of negative effects to them. Obviously, the mental health problems of college students not only directly affect their own growth, but also affect the stability of the campus. Most colleges also pay more and more attention to students' psychological crisis monitoring and prevention. All Colleges simply analyze whether students have mental health problems or what kind of problems they have. It cannot find hidden relationships in the psychological data. We need a system to handle the student mental health problems, here we are mainly concentrating on student stress prediction. There are so many factors related to stress such as workload, assignments, family issues, friends’ issues, attendance, teaching, etc. Machine learning is a subject to predict the future based on past data. Using machine learning techniques, we predict student stress levels, and also the proposed system will give suggestions based on the stress levels of students.

Keywords: Student stress levels, psychological data, machine learning.

PDF | DOI: 10.17148/IARJSET.2023.10537

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