Research Results on System Development of the Research Project of a Self-Study System for Language Learning

Katsuyuki Umezawa, Makoto Nakazawa, Manabu Kobayashi, Yutaka Ishii, Michiko Nakano, Shigeichi Hirasawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This study proposes to develop a self-study system equipped with an artificial instructor who detects and advises learners and evaluates their language learning in a consolidated framework. Detecting the learners mean that the self-study system understands their learning conditions. In this paper, we describe the results of system development among our projects. In particular, we describe a study that detects various errors necessary for a self-study system and propose a system for efficiently collecting EEG (brain waves), which are biological information for detecting the learners.

Original languageEnglish
Title of host publicationEDUNINE 2022 - 6th IEEE World Engineering Education Conference
Subtitle of host publicationRethinking Engineering Education After COVID-19: A Path to the New Normal, Proceedings
EditorsClaudio da Rocha Brito, Melany M. Ciampi
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665483360
DOIs
Publication statusPublished - 2022
Event6th IEEE World Engineering Education Conference, EDUNINE 2022 - Santos, Brazil
Duration: 2022 Mar 132022 Mar 16

Publication series

NameEDUNINE 2022 - 6th IEEE World Engineering Education Conference: Rethinking Engineering Education After COVID-19: A Path to the New Normal, Proceedings

Conference

Conference6th IEEE World Engineering Education Conference, EDUNINE 2022
Country/TerritoryBrazil
CitySantos
Period22/3/1322/3/16

Keywords

  • Java
  • Language Learning
  • Self-study System
  • Simple EEG
  • e-Learning

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Engineering (miscellaneous)
  • Education

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