This study is focused on the impact of coronavirus in education institutions by using datasets to prevent the virus from spreading; and the effects of lockout, which could result in mental health psychological issues such as anger, depression, and stress among students. this paper will study how using data mining to show the COVID-19's effect on students of various age groups: time spent on online classes and self-study, the medium used for learning, sleeping habits, daily fitness routine, and the subsequent effects on weight, social life, and mental health. The study showed 58.7% is the highest percentage of students that responded to the survey with different age groups. It also shows that the average accuracy of the Naïve Bayes model is 45.85%.