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Abstract

The COVID-19 pandemic significantly disrupted various sectors, with higher education being one of the most severely affected. Students in higher education faced numerous challenges transitioning to online learning, leading to a surge in mental health issues. The abrupt shift in the mode of education and the inability of many students to adapt exacerbated their mental health struggles. This, in turn, contributed to a notable rise in student suicide rates in India during the pandemic-induced isolation period. Addressing this critical socio-psychological issue requires effective strategies for stress detection and management. The proposed study employed the Online Education Stress Scale (Online ESS) to collect data from students enrolled in colleges affiliated with Dr. Bhimrao Ambedkar University, Agra. The research introduced a methodology to analyse stress levels by categorizing data into three primary stress factors. For each factor, a fuzzy inference system was developed. By applying fuzzy logic, the study tackled the imprecision and vagueness inherent in psychological data, providing a more reliable system for understanding the relationships between psychological variables and stress levels.

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