Applying Social Network Analysis on Courses relationship in Informatics Mathematics Curriculum

Abstract

This study investigates the relationship the courses achievement of undergraduate students in Informatics Mathematics curriculum. Social Network Analysis and Pearson product Moment Correlation Coefficient are used to determine which courses are significant important and influence predictors. Data collected is from the sample of 91 online report submitted by science graduated students who have graduated during the academic year 2010-2017. The results of the study indicate that Linear Algebra and Discrete Mathematics are the highest score of weighted degree centrality as Mathematics information technology is the highest score of betweenness centrality and English for informatics Mathematics influence over the whole courses.