Investigating co-occurrence patterns of learners' grammatical errors across proficiency levels and essay topics based on association analysis

Yutaka Ishii*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter is based on the framework of educational data mining (EDM). It focuses on the relationship between essay topics and co-occurrence patterns of learners' grammatical errors. The techniques of data mining shed light on learners' hidden association pattern of grammatical errors. Investigating learners' grammatical errors is a very important area in language teaching. In the past, this research was conducted only in the area of language teaching. However, in recent years, it has been conducted in the field of natural language processing such as the research on automated scoring of learners' writing or speaking and automated grammatical error detection. The subject 'English writing' was introduced to Japanese high schools after the curriculum was revised in 1989. Error analysis (EA) has been conducted since the 1950s because learners' errors can be considered as a benchmark for the proficiency in a language.

Original languageEnglish
Title of host publicationData Mining And Learning Analytics
Subtitle of host publicationApplications in Educational Research
PublisherWiley-Blackwell
Pages157-171
Number of pages15
ISBN (Electronic)9781118998205
ISBN (Print)9781118998236
DOIs
Publication statusPublished - 2016 Oct 14

Keywords

  • Automated grammatical error detection
  • Educational data mining
  • Error analysis
  • Grammatical structures
  • Japanese high schools
  • Language teaching

ASJC Scopus subject areas

  • General Computer Science

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