Investigating factors influencing scholastic execution at undergrad level using network analytics

Study of relationships/interactions among students and teachers in structured learning environments have been a keen area of interests among educational analysts since decades. These relationships have been found to have direct as well as indirect impacts on the performance of students through varied interdisciplinary researches. The study presented in this paper is a novel application of Social Network Analytics to deeply understand and quantify direct or indirect relational impacts on undergrad level student's scholastic execution in India. Undergrad Computer Science students from a class of Kalindi College are surveyed to pull-together information on varied relational parameters of student-student and student-teacher relationships for generating varied networks and deep analytical analysis using specialized graph (network) analytic software `Gephi'. The quantitative results generated with the help of `Gephi' software successfully signaled significant relational aspects which have direct impact on students's performance. The generated results hence can be utilized in various ways to target specific issues beforehand with the sole aim to improve student's performance. The presented study displays a scope for substantial future research and can help in leading to fresh perspectives in handling relationships data for decision making and reframing educational policies for betterment.