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Yun Long; Haifeng Luo; Yu Zhang – npj Science of Learning, 2024
This study explores the use of Large Language Models (LLMs), specifically GPT-4, in analysing classroom dialogue--a key task for teaching diagnosis and quality improvement. Traditional qualitative methods are both knowledge- and labour-intensive. This research investigates the potential of LLMs to streamline and enhance this process. Using…
Descriptors: Classroom Communication, Computational Linguistics, Chinese, Mathematics Instruction
Phuong-Anh Nguyen – IAFOR Journal of Education, 2024
Strategic competence, the ability to use communication strategies (CS) to overcome challenges and enhance communication effectiveness, is crucial in language learning. However, the coverage of these strategies as well as target models to teach them remain scarce in current instructional materials. This paper represents the first attempt to examine…
Descriptors: Artificial Intelligence, Computer Software, Metacognition, Technology Uses in Education
Song, Yu; Zhang, Shu; Liu, Bingman – Journal of Educational Research, 2023
Classroom dialogue is widely used in mathematics teaching and learning, and if managed strategically, it will have productive benefits for mathematics achievement. However, dialogic participants often lack awareness of how dialogue could be constructed, and few studies show the characteristics of dialogic patterns in different stages of education.…
Descriptors: Dialogs (Language), Mathematics Instruction, Comparative Analysis, Computer Software
Dixon, Daniel H. – CALICO Journal, 2022
This study quantitatively measures the variation in language derived from a targeted set of digital game mechanics. Mechanics refer to the design elements of a game that make up the overall gameplay experience, determining player actions and the degree of language interaction. A corpus was compiled by extracting the language files from two popular…
Descriptors: Language Usage, Computer Games, Second Language Learning, Second Language Instruction
Gloria Ashiya Katuka – ProQuest LLC, 2024
Dialogue act (DA) classification plays an important role in understanding, interpreting and modeling dialogue. Dialogue acts (DAs) represent the intended meaning of an utterance, which is associated with the illocutionary force (or the speaker's intention), such as greetings, questions, requests, statements, and agreements. In natural language…
Descriptors: Dialogs (Language), Classification, Intention, Natural Language Processing
Mazumder, Sahisnu – ProQuest LLC, 2021
Dialogue systems, commonly called as Chatbots, have gained escalating popularity in recent times due to their wide-spread applications in carrying out chit-chat conversations with users and accomplishing tasks as personal assistants. These systems are typically trained from manually-labeled data and/or written with handcrafted rules and often, use…
Descriptors: Computer Mediated Communication, Computer Software, Dialogs (Language), Information Seeking
Aldha Williyan; Sri Wuli Fitriati; Hendi Pratama; Zulfa Sakhiyya – Teaching English with Technology, 2024
This research explores the collaboration between Indonesian English as a Foreign Language (EFL) educators and Artificial Intelligence (AI) in content development. Employing a qualitative approach, semi-structured interviews were conducted to delve into the perspectives, experiences, and interactions of educators in the realm of AI-enhanced content…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Artificial Intelligence
Chen, Guanliang; Ferreira, Rafael; Lang, David; Gasevic, Dragan – International Educational Data Mining Society, 2019
For the development of successful human-agent dialogue-based tutoring systems, it is essential to understand what makes a human-human tutorial dialogue successful. While there has been much research on dialogue-based intelligent tutoring systems, there have been comparatively fewer studies on analyzing large-scale datasets of human-human online…
Descriptors: Student Attitudes, Intelligent Tutoring Systems, Computer Software, Dialogs (Language)
Song, Yu; Lei, Shunwei; Hao, Tianyong; Lan, Zixin; Ding, Ying – Journal of Educational Computing Research, 2021
Due to benefits for teaching and learning, an increasing number of studies have focused on classroom dialogue and how to make it productive. Coding, in which the transcribed conversation is allocated to a set of features, is commonly employed to deal with the textual data arising from this dialogue. This is generally done manually and cannot…
Descriptors: Semantics, Classification, Classroom Communication, Dialogs (Language)
McGowan, Ian S. – International Association for Development of the Information Society, 2020
Upto now, the knowledge building influence of the fundamental communicative functions during an on-line collaborative learning (OLCL) session, i.e. argumentative, responsive, elicitative, informative and imperative have been mainly based on results from qualitative studies, results that could have been strengthened by quantitative approaches.…
Descriptors: Higher Education, Online Courses, Cooperative Learning, Computer Science Education