Predictive Analysis Of Student Stress Level Using Machine Learning

Ranjitha Bai A; Harshitha V; Anil G; Manoj L S

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Submission Last date	28-Jun-2025
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Title: :  Predictive Analysis Of Student Stress Level Using Machine Learning
PaperId: :  24041
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 3 2024
DUI:    16.0415/IJARIIE-24041
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Name	Author Institute
Ranjitha Bai A	Vidya Vikas Institute of Engineering and Technology
Harshitha V	Vidya Vikas Institute of Engineering and Technology
Anil G	Vidya Vikas Institute of Engineering and Technology
Manoj L S	Vidya Vikas Institute of Engineering and Technology

Abstract

Research Area	Information Science and Engineering
KeyWord	somatization, interpersonal sensitivity, psychopathy, counselling
Abstract	College students are struggling with a lot of mental health issues, including stress, somatization, obsession, interpersonal sensitivity, depression anxiety, hostility, fear, paranoia, and psychopathy, which might have bad effects on them. The mental health problems of college students not just directly impact their development, but also affect the stability of campus. Most colleges pay more attention to students' crisis monitoring and prevention. All colleges just analyze whether students have mental health problems or what problems they are having. Some lectures doing manual counselling sitting with students and trying to identify mental health disorders for low academic performance. These systems cannot find hidden relationships in psychological data. We need a system to handle student mental health issues; here, we mainly emphasize student stress prediction. Many factors connected to stress like age, gender, workload, assignments, family issues, friend’s problems, attendance, teaching, etc…. Machine learning is a discipline that predicts the future based on past data. By using machine learning techniques, we predict student stress and levels, and the proposed system would offer recommendations based on students' stress levels. In this proposal system, we are developing automation for the education sector to predict student stress and levels. The proposed system is a browser-based application for colleges using Microsoft technologies such as Visual Studio, C#, and SQL Server.

Citations

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IJARIIE	Ranjitha Bai A, Harshitha V, Anil G, and Manoj L S. "Predictive Analysis Of Student Stress Level Using Machine Learning" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 3 2024 Page 2738-2744
MLA	Ranjitha Bai A, Harshitha V, Anil G, and Manoj L S. "Predictive Analysis Of Student Stress Level Using Machine Learning." International Journal Of Advance Research And Innovative Ideas In Education 10.3(2024) : 2738-2744.
APA	Ranjitha Bai A, Harshitha V, Anil G, & Manoj L S. (2024). Predictive Analysis Of Student Stress Level Using Machine Learning. International Journal Of Advance Research And Innovative Ideas In Education, 10(3), 2738-2744.
Chicago	Ranjitha Bai A, Harshitha V, Anil G, and Manoj L S. "Predictive Analysis Of Student Stress Level Using Machine Learning." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 3 (2024) : 2738-2744.
Oxford	Ranjitha Bai A, Harshitha V, Anil G, and Manoj L S. 'Predictive Analysis Of Student Stress Level Using Machine Learning', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 3, 2024, p. 2738-2744. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Predictive_Analysis_Of_Student_Stress_Level_Using_Machine_Learning_ijariie24041.pdf (Accessed : ).
Harvard	Ranjitha Bai A, Harshitha V, Anil G, and Manoj L S. (2024) 'Predictive Analysis Of Student Stress Level Using Machine Learning', International Journal Of Advance Research And Innovative Ideas In Education, 10(3), pp. 2738-2744IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Predictive_Analysis_Of_Student_Stress_Level_Using_Machine_Learning_ijariie24041.pdf (Accessed : )
IEEE	Ranjitha Bai A, Harshitha V, Anil G, and Manoj L S, "Predictive Analysis Of Student Stress Level Using Machine Learning," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 3, pp. 2738-2744, May-Jun 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/Predictive_Analysis_Of_Student_Stress_Level_Using_Machine_Learning_ijariie24041.pdf [Accessed : ].
Turabian	Ranjitha Bai A, Harshitha V, Anil G, and Manoj L S. "Predictive Analysis Of Student Stress Level Using Machine Learning." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 3 ().
Vancouver	Ranjitha Bai A, Harshitha V, Anil G, and Manoj L S. Predictive Analysis Of Student Stress Level Using Machine Learning. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(3) : 2738-2744. Available from: https://ijariie.com/AdminUploadPdf/Predictive_Analysis_Of_Student_Stress_Level_Using_Machine_Learning_ijariie24041.pdf

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