Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/119113
Title: | Data science for a new generation of tutors: building an academic-guidance system based on dropout and grades prediction |
Author: | Rovira Cisterna, Sergi |
Director/Tutor: | Igual Muñoz, Laura |
Keywords: | Dades massives Aprenentatge automàtic Programari Treballs de fi de grau Sistemes d'ajuda a la decisió Tutoria (Ensenyament) Big data Machine learning Computer software Bachelor's theses Decision support systems Tutoring (Teaching) |
Issue Date: | 26-Jan-2017 |
Abstract: | This work is part of an innovative educational project which aim is to create a tool to help tutors offer more personalised and proactive guidance to the students. An analysis of the performance of different Machine Learning techniques for dropout intention prediction is presented. The approach of using Recommender Systems for final grade prediction and course ranking creation has been also assessed. Visualizations which help in the interpretation of the obtained results have been developed and a design for the tutoring tool has been outlined. The research has been performed using data from the degree studies in Law, Computer Science and Mathematics of Universitat de Barcelona. |
Note: | Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2017, Director: Laura Igual Muñoz |
URI: | http://hdl.handle.net/2445/119113 |
Appears in Collections: | Programari - Treballs de l'alumnat Treballs Finals de Grau (TFG) - Enginyeria Informàtica |
Files in This Item:
File | Description | Size | Format | |
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codi_font.zip | Codi font | 1.36 MB | zip | View/Open |
memoria.pdf | Memòria | 4.8 MB | Adobe PDF | View/Open |
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