OAK

An AI-based English education platform during the COVID-19 pandemic

Metadata Downloads
Abstract
This study examines whether the use of AI-Pengtalk, an AI-based Conversational English programme, provided by a broadcasting company (EBS) that specializes in public education can significantly improve conversational English skills and bridge the English language proficiency gap associated with parental socioeconomic status. Over the course of four weeks from April 27 to May 22 in 2020, 108 fourth-grade classes in 54 elementary schools voluntarily participated in this experiment. Two classes in each school were designated as a treatment group and a control group. For the treatment group, a tablet installed with a pilot version of AI-Pengtalk was provided and students were encouraged to make use of the programme. Two sets of surveys and English tests were placed pre and post hoc. After 4 weeks, test scores, log files, and survey responses of participants were analysed. A series of DID analyses demonstrate that the use of AI-Pengtalk improves the treatment group's self-evaluation of their English abilities, confidence in using English, preference on English itself, and amount of time spent on studying English during the pilot experimental period compared to the control group. When other variables were controlled, the use of AI-Pengtalk also helped the treatment group achieve higher test scores. This study implicates that the use of smart English education like AI-Pengtalk may especially be able to better compensate for academic setbacks caused by low parental SES or, in the case of English learning, the reluctance to converse in English with other students.
Author(s)
Um, HansukKim, HisamChoi, DainOh, Hyungna
Issued Date
2024-08
Type
Article
DOI
10.1007/s10209-023-01046-2
URI
https://scholar.gist.ac.kr/handle/local/9448
Publisher
SPRINGER HEIDELBERG
Citation
UNIVERSAL ACCESS IN THE INFORMATION SOCIETY, v.23, no.3, pp.1233 - 1248
ISSN
1615-5289
Appears in Collections:
School of Humanities and Social Sciences > 1. Journal Articles
공개 및 라이선스
  • 공개 구분공개
파일 목록

Items in Repository are protected by copyright, with all rights reserved, unless otherwise indicated.