engleski

Visualization and Prediction of Students’ Course Progress

Our presentation has two goals. The first goal of our presentation is to visualize students’ course progress. For successful accomplishment of the goal we need to present multi- dimensional data in a simple way and detect groups of students with similar progress pattern. Among others, logistic regression and linear discriminant analysis will be presented as methods for supervised learning, also useful for prediction of future students’ progress through course. Presentation of the methods is the second goal of our presentation. Analysis and visualizations are presented using data about the students’ progress during the course Financial mathematics for two sequential academic years, 2014/2015 and 2015/2016. Visualization of the progress data is done using R programming language and appropriate packages.

data visualization ; logistic regression ; predictive analytics ; learning analytics

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