@InProceedings{chinkina-meurers:2017:BEA,
  author    = {Chinkina, Maria  and  Meurers, Detmar},
  title     = {Question Generation for Language Learning: From ensuring texts are read to supporting learning},
  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     = {334--344},
  abstract  = {In Foreign Language Teaching and Learning (FLTL), questions are systematically
	used to assess the learner’s understanding of a text. Computational
	linguistic approaches have been developed to generate such questions
	automatically given a text (e.g., Heilman, 2011). In this paper, we want to
	broaden the perspective on the different functions questions can play in FLTL
	and discuss how automatic question generation can support the different uses.
	Complementing the focus on meaning and comprehension, we want to highlight the
	fact that questions can also be used to make learners notice form aspects of
	the linguistic system and their interpretation. Automatically generating
	questions that target linguistic forms and grammatical categories in a text in
	essence supports incidental focus-on-form (Loewen, 2005) in a meaning-focused
	reading task. We discuss two types of questions serving this purpose, how they
	can be generated automatically; and we report on a crowd-sourcing evaluation
	comparing automatically generated to manually written questions targeting
	particle verbs, a challenging linguistic form for learners of English.},
  url       = {http://www.aclweb.org/anthology/W17-5038}
}