RevUP: Automatic gap-fill question generation from educational texts

Kumar, Girish and Banchs, Rafael E. and D'Haro Enriquez, Luis Fernando (2015). RevUP: Automatic gap-fill question generation from educational texts. In: "10th Workshop on Innovative Use of NLP for Building Educational Applications", 31/05/2015 - 05/06/2015, Denver, Colorado, USA. pp. 154-161.

Description

Title: RevUP: Automatic gap-fill question generation from educational texts
Author/s:
  • Kumar, Girish
  • Banchs, Rafael E.
  • D'Haro Enriquez, Luis Fernando
Item Type: Presentation at Congress or Conference (Article)
Event Title: 10th Workshop on Innovative Use of NLP for Building Educational Applications
Event Dates: 31/05/2015 - 05/06/2015
Event Location: Denver, Colorado, USA
Title of Book: 10th Workshop on Innovative Use of NLP for Building Educational Applications
Date: 2015
Subjects:
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (138kB) | Preview

Abstract

This paper describes RevUP which deals with automatically generating gap-fill questions. RevUP consists of 3 parts: Sentence Selection, Gap Selection & Multiple Choice Distractor Selection. To select topicallyimportant sentences from texts, we propose a novel sentence ranking method based on topic distributions obtained from topic models. To select gap-phrases from each selected sentence, we collected human annotations, using the Amazon Mechanical Turk, on the relative relevance of candidate gaps. This data is used to train a discriminative classifier to predict the relevance of gaps, achieving an accuracy of 81.0%. Finally, we propose a novel method to choose distractors that are semantically similar to the gap-phrase and have contextual fit to the gap-fill question. By crowdsourcing the evaluation of our method through the Amazon Mechanical Turk, we found that 94% of the distractors selected were good. RevUP fills the semantic gap left open by previous work in this area, and represents a significant step towards automatically generating quality tests for teachers and self-motivated learners.

More information

Item ID: 42192
DC Identifier: http://oa.upm.es/42192/
OAI Identifier: oai:oa.upm.es:42192
Official URL: http://www.aclweb.org/anthology/W15-0618
Deposited by: Memoria Investigacion
Deposited on: 24 Jul 2016 08:21
Last Modified: 24 Jul 2016 08:21
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM