Understanding Vocabulary Growth Through An Adaptive Language Learning System

Open Access
Authors
  • Y. Qiao
  • C. Kohlschein
  • T. Meisen
Publication date 2019
Host editors
  • D. Alfter
  • E. Volodina
  • L. Borin
  • I. Pilan
  • H. Lange
Book title Proceedings of the 8th Workshop for Natural Language Processing for Computer-Assisted Language Learning
Book subtitle NLP4CALL 2019
Series NEALT Proceedings Series
Event 8th Workshop for Natural Language Processing for Computer-Assisted Language Learning
Pages (from-to) 65-78
Publisher Linköping: LiU Electronic Press
Organisations
  • Faculty of Humanities (FGw)
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract
Learning analytics and educational data mining have gained an increased interest as an important way of understanding the way humans learn. The paper introduces an adaptive language learning system designed to track and accelerate the development of academic vocabulary skills thereby generating dense longitudinal data of individual vocabulary growth trajectories. We report on an exploratory study based on the dense longitudinal data obtained from our system. The goal is the study was twofold: (1) to examine the pace and shape of vocabulary growth trajectories and (2) to understand the role various individual differences factors play in explaining variation in such growth trajectories.
Document type Chapter
Language English
Published at https://www.aclweb.org/anthology/W19-6307/
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