Effects of co-curricular activities on student's academic performance by machine learning

• Published in: Current research in behavioral sciences 2021-11, Vol.2, p.100057, Article 100057
• Main Authors: Rahman, Shaikh Rezwan, Islam, Md. Asfiul, Akash, Pritidhrita Paul, Parvin, Masuma, Moon, Nazmun Nessa, Nur, Fernaz Narin
• Format: Article
• Language: English
• Subjects: Academic performance; Co-curricular activity; Involvement; Relation; result; Survey
• ISSN: 2666-5182; 2666-5182
• DOI: 10.1016/j.crbeha.2021.100057

•Focusing on the co-curricular activities on a student's result.•Intention to find the relation between co-curricular activities and student's result.•Data analysis and data visualization and different algorithms have been applied to the collected dataset to find the correlation between co-curricular activities and the student's result.•The effect was measured by collecting the data from students with some relevant questions.•Different ML algorithms helped this paper to find a positive correlation between the co-curricular activities and student's academic performance. The study project named "Effects of Co-Curricular Activities on Student's Academic Performance Through Machine Learning" examines the effect of co-curricular activities on a student's academic performance. The purpose of this study is to determine the relationship between extracurricular activities and student performance. Co-curricular activities are extracurricular activities that support and enhance the academic or core curriculum. They are a vital component of educational institutions' attempts to help students develop their personalities and improve classroom learning. However, a significant proportion of pupils in Bangladesh do not participate in such activities. One of the primary reasons is because many believe these activities would jeopardize a student's academic performance. This study's objective is to ascertain the actual effect of co-curricular activities on pupils. It was discovered that there is a positive correlation between co-curricular activities and academic performance using Logistic Regression using Python and Google Colab. A study on the impact of the cocurricular activity on the results of a pupil is concentrated on the "Effects of Co-Curricular Activities on Student's Academic Performance by Machine Learning". The goal is to establish a relationship between co-learning and student outcomes. Co-curricular activities are described as activities that enable the curricular or key curriculum to be strengthened and improved. They are the essential foundation for the identity of the pupil and promote the learning of the classroom. But Bangladesh does not include a very big number of students. One of the key factors being that people believe these practices would hinder the academic success of a pupil. Therefore, the real effects of co-worker interactions on students are necessary to be discovered. By using Python and Google Colab for Logistic Rectification it was discovere