Predictive Learning Analytics

Bachelor Thesis (2019)
Author(s)

W.R.A. Turk (TU Delft - Electrical Engineering, Mathematics and Computer Science)

F.A. Ooijevaar (TU Delft - Electrical Engineering, Mathematics and Computer Science)

R.J. Faber (TU Delft - Electrical Engineering, Mathematics and Computer Science)

M. Al Nahadi (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

N. Yorke-Smith – Mentor (TU Delft - Algorithmics)

O.W. Visser – Graduation committee member (TU Delft - Computer Science & Engineering-Teaching Team)

Joost Verdoorn – Mentor

Bas Hintemann – Mentor

Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright
© 2019 Wessel Turk, Frank Ooijevaar, Robin Faber, Murtadha Al Nahadi
More Info
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Publication Year
2019
Language
English
Copyright
© 2019 Wessel Turk, Frank Ooijevaar, Robin Faber, Murtadha Al Nahadi
Graduation Date
04-07-2019
Awarding Institution
Delft University of Technology
Project
['Bachelor End Project']
Programme
['Computer Science']
Faculty
Electrical Engineering, Mathematics and Computer Science
Reuse Rights

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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.

Files

Final_Report_BEP.pdf
(pdf | 0.946 Mb)
License info not available