CoChat
Sign Up
Cited by 434EFL/ESL Teaching and LearningEnglish Language Learning and TeachingAI in Service Interactions

The DOI matches its Crossref record, with a small difference in title or year; 43 of the 43 references it cites were found in a registry or an index.

Exploring AI chatbot affordances in the EFL classroom: young learners’ experiences and perspectives

Jeon, Jaeho·2024·Computer Assisted Language Learning
DOI 10.1080/09588221.2021.2021241
Open this paper in CoChat — free account

Abstract

Professionals within the field of language learning have predicted that chatbots would provide new opportunities for the teaching and learning of language. Despite the assumed benefits of utilizing chatbots in language classrooms, such as providing interactional chances or helping to create an anxiety-free atmosphere, little is known about learners’ actual use of chatbots during language classes or how chatbots affect their motivation to learn a language. To address these gaps, this exploratory study aimed to create an inventory of affordances that chatbots provide in the primary English as a foreign language (EFL) classroom and to explore how the affordances affect psychological aspects in language learners, particularly regarding their motivation to learn English through chatbots. Thirty-six Korean primary school learners participated in a 16-week EFL course that utilized customized chatbots. These chatbots were created using Google’s Dialogflow. After the course, individual in-depth interviews were conducted regarding the participants’ experiences and perceptions of the chatbots. Student-chatbot interaction logs produced during the course were also collected to supplement the interview data. Qualitative analysis of the interview transcripts and interaction logs revealed the presence of pedagogical, technological, and social affordances. Depending on the learner, the chatbot affordances were perceived differently; thus, each affordance acted as either an opportunity or a constraint for English language learning. In addition, this study specifically discussed how these chatbot affordances might have affected psychological states in language learners. Future recommendations regarding the use of chatbots in language classrooms were suggested from both pedagogical and technological perspectives.

Overview

Integrity signals

Registry

Crossref · 10.1080/09588221.2021.2021241

Cites

43 of 43 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 42 references

Research works printed but not linked: 5

  1. AlKhayat, A. (2017). Exploring the effectiveness of using chatbots in the EFL classroom. In P. Hubbard & S. Ioannou-Georgiou (Eds.),Teaching English reflectively with technology (pp. 20–36). IATEFL.
  2. Atwell, E. (1999). The language machine: The impact of speech and language technologies on English language teaching. British Council.
  3. Gibson, J. J. (1986). The ecological approach to visual perception. Lawrence Earlbaum.
  4. 10.1007/978-3-030-34212-8 · DOI
  5. 10.1007/978-3-030-34212-8 · DOI

Cited by

Sorted by citations

Related

See all

Metadata

Authors
Jeon, J.
Affiliations
Seoul National University of Education (KR)
Corresponding author
Jeon, Jaeho
ORCID
Jeon, Jaeho
Venue
Computer Assisted Language Learning
Publisher
Informa UK Limited
Published
2022-01-10
Volume
37
Issue
1-2
Pages
1-26
ISSN
  • 0958-8221 (ISSN-L)
  • 1744-3210
DOI
10.1080/09588221.2021.2021241
OpenAlex
W4206806123
Semantic Scholar
f396762bc127f3411128fa0f6db5cbf3d5594bb5
Cited by
433
References
42
Citations by year
2026: 149 · 2025: 134 · 2024: 102 · 2023: 40 · 2022: 8
FWCI
267.24
Type
journal article
Language
en
Open access
closed
Locations
Computer Assisted Language Learning (publishedVersion)
Topics
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
  • Social Sciences › Education › English Language Learning and Teaching
  • Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
Keywords
chatbots, affordances, English as a foreign language, elementary school students, student motivation, student experience, Dialogflow, pedagogical affordances, technology affordances, social affordances, Korean language learners

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review