Evidence map›Paper›PMID 41982350›Full record

ArticleFrontiers in psychology2026

Simulating the "cultural other": the impact of GenAI interlocutors on EFL learners' intercultural communicative competence, speaking anxiety, and learning engagement.

Zhanbo Qu, Liyun Chen

Abstract read
In one paragraph

Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Zhanbo QuSchool of Foreign Languages, Northwest Minzu University, Lanzhou, Gansu, China.
Liyun ChenSchool of Foreign Languages, Longnan Normal University, Longnan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Peer role-play is a widely used pedagogical strategy for fostering intercultural communicative competence (ICC), yet its effectiveness is often limited by the lack of authentic cultural context and the prevalence of foreign language speaking anxiety. This study, therefore, examines the potential of voice-based generative AI (GenAI) as a scalable, high-fidelity alternative. Method: Using a quasi-experimental design, two intact classes of undergraduate EFL learners in China were assigned to either a GenAI-partnered experimental group ( Results and discussion: Quantitative results showed that the experimental group significantly outperformed the control group in both intercultural speaking performance and perceived ICC. Learners interacting with GenAI also reported a significantly greater reduction in speaking anxiety. ENA revealed a cohesive socio-cognitive triangle in learners' engagement patterns, characterized by the integration of social politeness, cognitive repair, and proactive topic extension. Qualitative findings further indicated that learners experienced the GenAI environment as a psychologically safe space that encouraged risk-taking and as a cultural informant that provided just-in-time pragmatic feedback, despite perceived limitations related to missing paralinguistic cues. Overall, the study suggests that GenAI interlocutors can effectively simulate a culturally distinct "other," offering a psychologically safe and cognitively engaging pathway for ICC development. It argues for the systematic incorporation of AI-scaffolded intercultural practice alongside, and in some cases in place of, traditional peer-based activities in EFL and L2 curricula.

Indexed as

EFLforeign language speakinggenerative AI (GenAI)human-AI interactionintercultural communicative competence (ICC)learning engagementspeaking anxiety

Identifiers

PMID41982350
PMCPMC13071047

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.