@inproceedings{b16dc27798aa4a52b5adc06b93eca178,
title = "Profiling Student Interactions in Threaded Discussions with Speech Act Classifiers",
abstract = "On-line discussion is a popular form of web-based computer-mediated communication and is an important medium for distance education. Automatic tools for analyzing online discussions are highly desirable for better information management and assistance. This paper presents an approach for automatically profiling student interactions in on-line discussions. Using N-gram features and linear SVM, we developed “speech act” classifiers that identify the roles that individual messages play. The classifiers were used in finding messages that contain questions or answers. We then applied a set of thread analysis rules for identifying threads that may have unanswered questions and need instructor attention. We evaluated the results with three human annotators, and 70-75% of the predictions from the system were consistent with human answers.",
keywords = "discussion assessment, On-line discussion board, speech act",
author = "Sujith Ravi and Jihie Kim",
note = "Publisher Copyright: {\textcopyright} 2007 The authors and IOS Press. All rights reserved.; 13th International Conference on Artificial Intelligence in Education, AIED 2007 ; Conference date: 09-07-2007 Through 13-07-2007",
year = "2007",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "357--364",
editor = "Rosemary Luckin and Koedinger, {Kenneth R.} and Jim Greer",
booktitle = "Artificial Intelligence in Education",
address = "Netherlands",
}