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Showing 1 - 9 results of 9 for Timpe-Laughlin

Openings and closings in human-human versus human-spoken dialogue system conversations

by Judit Dombi, Tetyana Sydorenko, Veronika Timpe-Laughlin
in Volume 28 Number 2, June 2024 Special Issue: Artificial Intelligence for Language Learning

Using an AI-powered chatbot for improving L2 Korean grammar: A comparison between proficiency levels and task types
...Timpe-Laughlin & Dombi, 2020) and fewer instances of turn-taking, clarification, and backchanneling (Timpe-Laughlin et al., 2024). Similar implications might apply to comparisons with synchronous co...

by Ji-young Shin, Yujeong Choi
in Volume 29 Number 2, February 2025 Special Issue: Indigenous Languages and Less Commonly Taught Languages (LCTLs) with Technology

Emerging spaces for language learning: AI bots, ambient intelligence, and the metaverse
...Timpe-Laughlin et al., 2022). Studies also have demonstrated that scripted dialog systems can be used effectively in setting up role plays for pragmatic language learning (Dombi et al., 2022; Timpe-...

by Robert Godwin-Jones
in Volume 27 Number 2, February 2023 Special Issue: Semiotics in CALL

L2 pragmatics and CALL
...Timpe-Laughlin et al. (2017), these SDS provide environments effective for L2 pragmatic learning because they allow for the design of specific pragmatic foci, provide learners with authentic and rel...

by Marta González-Lloret
in Volume 25 Number 3, October 2021 Special Issue: 25 Years of Emerging Technology in CALL

Artificial intelligence for language learning: Entering a new era
...Timpe-Laughlin, V. (2024). Openings and closing in human-human versus human-spoken dialogue system conversations. Language Learning & Technology, 28(2). 32–61. https://hdl.handle.net/10125/73571 Hu...

by Mark Warschauer, Ying Xu
in Volume 28 Number 2, June 2024 Special Issue: Artificial Intelligence for Language Learning

Teaching foreign language with conversational AI: Teacher-student-AI interaction
...Timpe-Laughlin et al., 2022). The inter-rater reliability was 93.45% and 93.25% for the first and second classes, respectively. Disagreements were resolved through discussion until 100% agreement wa...

by Hyangeun Ji, Insook Han, Soyeon Park
in Volume 28 Number 2, June 2024 Special Issue: Artificial Intelligence for Language Learning

Computer-assisted pronunciation training for foreign language learning of grammatical features
...Timpe-Laughlin et al., 2020; Tsai, 2019), highlighting the necessity for conversational agents, pronunciation scoring systems, mispronunciation detection tools, and CAPT systems. With the rapid de...

by Elsayed Issa, Gus Hahn-Powell
in Volume 29 Number 1, 2025

Investigating pragmatic learning opportunities and outcomes in different SCMC modes
...Timpe-Laughlin et al.’s work (2021), supplemented by Chen and Lin (2021). PREs were categorized into explicit and implicit dimensions. The explicit PREs were further sub-categorized according to the...

by Yuchen Peng, Yuhong Lei
in Volume 29 Number 3, October 2025 Special Issue: Multimodality in CALL

Teacher role in synchronous oral interaction: Young learner telecollaboration
...Timpe-Laughlin, 2021, p.28-9). Such findings support a widespread move to the action-based approach adopted in the Common European Framework of Reference for Languages (CEFR, Council of Europe, 2001...

by Ciara R. Wigham, Shona Whyte
in Volume 28 Number 1, 2024