Type : Conference Proceedings
Year : 2013
Secondary Title : Proc. of the 16th Conference on Artificial Intelligence in Education (AIED 2013)
Place Published : Memphis, TN
Publisher : Springer Berlin Heidelberg
Volume : 7926
Pages : 229-238
Tertiary Title : Lecture Notes in Computer Science
Date : "jul"
ISBN : 978-3-642-39111-8
Abstract : In this paper, we explore the potential of gaze data as a source of information to predict learning as students interact with MetaTutor, an ITS that scaffolds self-regulated learning. Using data from 47 college students, we show that a classifier using a variety of gaze features achieves considerable accuracy in predicting student learning after seeing gaze data from the complete interaction. We also show promising results on the classifier ability to detect learning in real-time during interaction.
Notes : 10.1007/978-3-642-39112-5_24
Authors : Bondareva, Daria Conati, Cristina Feyzi-Behnagh, Reza Harley, Jason M. Azevedo, Roger Bouchet, François
Editors : Lane, H. Chad Yacef, Kalina Mostow, Jack Pavlik, Philip