Boosting the Learning Process with Progressive Performance Prediction
Carlos Villagrá-Arnedo, Francisco J. Gallego-Durán, Rafael Molina-Carmona and Faraón Llorens-Largo
Departamento de Ciencia de la Computación e Inteligencia Artificial
Universidad de Alicante

10th European Conference on Technology Enhanced Learning (EC-TEL 2015)
Toledo, Spain, September 15-18, 2015
http://www.ec-tel.eu

Actas:
Design for Teaching and Learning in a Networked World
Lecture Notes in Computer Science 9307 (LNCS 9307)
http://www.springer.com/gp/book/9783319242576

Acceso al artículo

Abstract.
A prediction system to early detect learning problems is presented. The starting point is a gamified learning system from which a massive set of usage and learning data is collected. They are analyzed using Machine Learning techniques and a prediction of each student’s performance is obtained. The information is weekly presented as a progression chart, with valuable information about students’ progression. The system has a high degree of automation, is progressive, uses learning outcomes as well as usage data, allows the evaluation and prediction of the acquired skills, and contributes to a truly formative assessment.

Keywords:
Performance prediction · Machine learning · Gamified systems · Automatic assessment · Learning process

Póster: