Predictive Learning Analytics

Bachelor thesis (2019)

Authors

W.R.A. Turk Electrical Engineering, Mathematics and Computer Science
F.A. Ooijevaar Electrical Engineering, Mathematics and Computer Science
R.J. Faber Electrical Engineering, Mathematics and Computer Science
M. Al Nahadi Electrical Engineering, Mathematics and Computer Science

Contributors

N. Yorke-Smith Algorithmics - EEMCS (mentor)
O.W. Visser Computer Science & Engineering-Teaching Team - EEMCS (graduation committee member)
Joost Verdoorn (mentor)
Bas Hintemann (mentor)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2019 Wessel Turk, Frank Ooijevaar, Robin Faber, Murtadha Al Nahadi
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Published Date

04-07-2019

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

This report concludes the project 'Predictive Learning Analytics' for FeedbackFruits. It includes all the work that has been done in a ten week span at FeedbackFruits. FeedbackFruits is a company inspired to help teachers shape learning activities and spark students' active thinking, by creating an online platform on which teachers can create interactive learning activities. The goal for this project was to extend the analytics tools for interactive presentations that are offered to teachers who use the platform. This hopefully results in giving them more insight in the participation of the class, understanding of the course material and the effort that students put in their school work.