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Effects of speech-enabled LLM-based chatbots on L2 learning outcomes and affective domains: a multilevel meta-analysis
- Truvace record
- TRV-2026-2743raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Systematic review or meta-analysis
- Sources
- 1 sourcePeer-reviewed
- sha256
- 3941b6b326fe…check it
Abstract Recent developments in natural language processing and automatic speech recognition have significantly advanced chatbot communication using the voice mode, establishing these tools as viable resources for L2 speaking practice. More recently, the L2 chatbot domain has leveraged large language models (LLMs) to enhance contextual understanding and facilitate meaningful dialogues, prompting research into the effects of speech- and LLM-based chatbots on L2 learning outcomes and affective domains. This study…
The gain
A meta-analysis of 19 studies (32 samples, 2,643 learners) found speech-enabled LLM chatbots were linked to a pooled effect size of 0.68 on second-language learning outcomes and 0.64 on affective measures.
Sources
1 on file- International Review of Applied Linguistics in Language Teachingdoi:10.1515/iral-2026-0172
Cite this record
v1Truvace Impact Record TRV-2026-2743, v1: “Effects of speech-enabled LLM-based chatbots on L2 learning outcomes and affective domains: a multilevel meta-analysis.” Truvace, 2026-11-12. /record/TRV-2026-2743 (accessed on the day you copy it). sha256 3941b6b326fefa35…
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