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Muhammad Mooneeb Ali; Ahmed M. Alaa; Wael Alharbi; Issa Al Qurashi – International Journal of Technology in Education, 2025
Machine and prompt-based Artificial Intelligence (AI) learning has made significant evolution profusely. In education, it has revitalized researchers and educators to scout out subsequent advantages for optimizing learning results. Chiefly, Generative AI has exhibited substantial potential as a tool for language augmentation. This study aims to…
Descriptors: Foreign Countries, Grade 10, Artificial Intelligence, Natural Language Processing
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Feiwen Xiao; Ellen Wenting Zou; Jiaju Lin; Zhaohui Li; Dandan Yang – British Journal of Educational Technology, 2025
Large language model (LLM)-based conversational agents (CAs), with their advanced generative capabilities and human-like conversational interfaces, can serve as reading partners for children during dialogic reading and have shown promise in enhancing children's comprehension and conversational skills. However, there is limited research on the…
Descriptors: Childrens Literature, Electronic Books, Artificial Intelligence, Natural Language Processing
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Timpe-Laughlin, Veronika; Sydorenko, Tetyana; Daurio, Phoebe – Computer Assisted Language Learning, 2022
Often, second/foreign (L2) language learners receive little opportunity to interact orally in the target language. Interactive, conversation-based spoken dialog systems (SDSs) that use automated speech recognition and natural language processing have the potential to address this need by engaging learners in meaningful, goal-oriented speaking…
Descriptors: Second Language Learning, Second Language Instruction, Oral Language, Dialogs (Language)
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Chukharev-Hudilainen, Evgeny; Ockey, Gary J. – ETS Research Report Series, 2021
This paper describes the development and evaluation of Interaction Competence Elicitor (ICE), a spoken dialog system (SDS) for the delivery of a paired oral discussion task in the context of language assessment. The purpose of ICE is to sustain a topic-specific conversation with a test taker in order to elicit discourse that can be later judged to…
Descriptors: Intercultural Communication, Oral Language, Communicative Competence (Languages), Error Analysis (Language)
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Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun – Research-publishing.net, 2018
This paper presents a rule-based task-oriented dialogue system for second language learning and a knowledge extraction method which automatically extracts the training data for Natural Language Understanding (NLU) and dialogue rules for dialogue management from a Dialogue Map (DM). The DM consists of turn-by-turn utterances between the system and…
Descriptors: Graphs, Second Language Learning, Second Language Instruction, English (Second Language)
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Vlugter, P.; Knott, A.; McDonald, J.; Hall, C. – Computer Assisted Language Learning, 2009
We describe a computer assisted language learning (CALL) system that uses human-machine dialogue as its medium of interaction. The system was developed to help students learn the basics of the Maori language and was designed to accompany the introductory course in Maori running at the University of Otago. The student engages in a task-based…
Descriptors: College Students, Introductory Courses, Malayo Polynesian Languages, Pretests Posttests
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Rypa, Marikka Elizabeth; Price, Patti – CALICO Journal, 1999
Describes the Voice Interactive Training System (VILTS), a language-training prototype developed to help improve comprehension and speaking skills. The system incorporates two related technologies: speech recognition and pronunciation scoring. Discusses the motivation for the program, the interdisciplinary efforts involved, and the resulting…
Descriptors: Cognitive Style, Communicative Competence (Languages), Computer Assisted Instruction, Computer Software Evaluation