@inproceedings{2bb0e74341784b90878ad76676d2e97a,
title = "A low-cost scalable solution for monitoring affective state of students in e-learning environment using mouse and keystroke data",
abstract = "This study proposed a user-independent intelligent system that reports the affective state of students in a non-intrusive and low-cost manner by utilizing mouse record and keystroke data collected in dynamic world. A scalable client-server architecture for student affective state monitoring in e-learning environment is also demonstrated.",
keywords = "Affect Detection, Client-Server Architecture, E-learning, Keystroke, Mouse Record",
author = "Lee, {Po Ming} and Tsui, {Wei Hsuan} and Tzu-Chien Hsiao",
year = "2012",
doi = "10.1007/978-3-642-30950-2_118",
language = "English",
isbn = "9783642309496",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "679--680",
booktitle = "Intelligent Tutoring Systems - 11th International Conference, ITS 2012, Proceedings",
note = "11th International Conference on Intelligent Tutoring Systems, ITS 2012 ; Conference date: 14-06-2012 Through 18-06-2012",
}