@InProceedings{lugini-litman:2017:BEA,
  author    = {Lugini, Luca  and  Litman, Diane},
  title     = {Predicting Specificity in Classroom Discussion},
  booktitle = {Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {52--61},
  abstract  = {High quality classroom discussion is important to student development,
	enhancing
	abilities to express claims, reason about other students’ claims, and retain
	information for longer periods of time. Previous small-scale studies have shown
	that one indicator of classroom discussion quality is specificity. In this
	paper we tackle the problem of predicting specificity for classroom
	discussions. We propose several methods and feature sets capable of
	outperforming the state of the art in specificity prediction. Additionally, we
	provide a set of meaningful, interpretable features that can be used to analyze
	classroom discussions at a pedagogical level.},
  url       = {http://www.aclweb.org/anthology/W17-5006}
}