@InProceedings{renduchintala-koehn-eisner:2017:CoNLL,
  author    = {Renduchintala, Adithya  and  Koehn, Philipp  and  Eisner, Jason},
  title     = {Knowledge Tracing in Sequential Learning of Inflected Vocabulary},
  booktitle = {Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017)},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {238--247},
  abstract  = {We present a feature-rich knowledge tracing method that captures a student's
	acquisition and retention of knowledge during a foreign language phrase
	learning task. We model the student's behavior as making predictions under a
	log-linear model, and adopt a neural gating mechanism to model how the student
	updates their log-linear parameters in response to feedback.  The gating
	mechanism allows the model to learn complex patterns of retention and
	acquisition for each feature, while the log-linear parameterization results in
	an interpretable knowledge state. We collect human data and evaluate several
	versions of the model.},
  url       = {http://aclweb.org/anthology/K17-1025}
}