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Pierre-Alexandre Balland; Olesya Grabova; J. Scott Marcus; Robert Praas; Andrea Renda – European Union, 2025
This report examines the burgeoning generative artificial intelligence (GenAI) and foundation models landscape within the European Union, and analyses its impact, technological advancements, and regulatory implications. It details the GenAI value chain, identifying key players and investment trends, revealing a significant US dominance. The report…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Industry
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Erik Voss; Hansun Zhang Waring – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2025
Significant advancements in voice chatbots have spurred interest into their role in second language learning (Conium, 2008), particularly their ability to assist in the development of learners' conversation skills in a target language. Many efforts have been made to explore AI's potential to act as conversation partners for language learners. Of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Mediated Communication, Man Machine Systems
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Sukan Saeliang; Pinanta Chatwattana – International Education Studies, 2025
The project-based learning model via generative artificial intelligence, or PjBL model via Gen-AI, is a research tool that was initiated based on the concept of project-based learning management focusing mainly on self-directed learning, in which learners are able to learn and practice through the projects they are interested in as to their…
Descriptors: Active Learning, Student Projects, Artificial Intelligence, Man Machine Systems
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Stefan E. Huber; Kristian Kiili; Steve Nebel; Richard M. Ryan; Michael Sailer; Manuel Ninaus – Educational Psychology Review, 2024
This perspective piece explores the transformative potential and associated challenges of large language models (LLMs) in education and how those challenges might be addressed utilizing playful and game-based learning. While providing many opportunities, the stochastic elements incorporated in how present LLMs process text, requires domain…
Descriptors: Artificial Intelligence, Language Processing, Models, Play
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Ekaterina Tour; Mark Pegrum; Shem Macdonald – English Australia Journal, 2025
As artificial intelligence (AI), and especially generative AI, are increasingly impacting daily life, it is becoming essential for learners to acquire AI literacy -- the capability to interact with AI at the interface of technology and the target language. Without AI literacy, they may struggle to navigate AI-driven systems and access benefits of…
Descriptors: English Learners, Technology Uses in Education, Educational Strategies, Artificial Intelligence
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Jeon, Jaeho; Lee, Seongyong – Education and Information Technologies, 2023
Artificial Intelligence (AI) is developing in a manner that blurs the boundaries between specific areas of application and expands its capability to be used in a wide range of applications. The public release of ChatGPT, a generative AI chatbot powered by a large language model (LLM), represents a significant step forward in this direction.…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Models
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Michael Agyemang Adarkwah – Adult Learning, 2025
Adult learners are a neglected species in the generative artificial intelligence (GenAI) era. The sweeping changes brought by GenAI in the educational arena have implications for adult learning. GenAI in education will usher in a world of adult learning that will be radically different from its predecessor. However, how adult learners will apply…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Adult Learning
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Belda-Medina, Jose; Kokošková, Vendula – International Journal of Educational Technology in Higher Education, 2023
Recent advances in Artificial Intelligence (AI) have paved the way for the integration of text-based and voice-enabled chatbots as adaptive virtual tutors in education. Despite the increasing use of AI-powered chatbots in language learning, there is a lack of studies exploring the attitudes and perceptions of teachers and students towards these…
Descriptors: Technology Integration, Technology Uses in Education, Artificial Intelligence, Man Machine Systems
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Charlotte N. Gunawardena; Yan Chen; Nick Flor; Damien Sánchez – Online Learning, 2023
Gunawardena et al.'s (1997) Interaction Analysis Model (IAM) is one of the most frequently employed frameworks to guide the qualitative analysis of social construction of knowledge online. However, qualitative analysis is time consuming, and precludes immediate feedback to revise online courses while being delivered. To expedite analysis with a…
Descriptors: Models, Learning Processes, Knowledge Level, Online Courses
Rajkumar, Rajakrishnan – ProQuest LLC, 2012
Natural Language Generation (NLG) is the process of generating natural language text from an input, which is a communicative goal and a database or knowledge base. Informally, the architecture of a standard NLG system consists of the following modules (Reiter and Dale, 2000): content determination, sentence planning (or microplanning) and surface…
Descriptors: Natural Language Processing, Linguistics, Language Processing, Models
Kazemzadeh, Abe – ProQuest LLC, 2013
This dissertation studies how people describe emotions with language and how computers can simulate this descriptive behavior. Although many non-human animals can express their current emotions as social signals, only humans can communicate about emotions symbolically. This symbolic communication of emotion allows us to talk about emotions that we…
Descriptors: Natural Language Processing, Psychological Patterns, Computer Simulation, Discourse Analysis
Ezen-Can, Aysu; Boyer, Kristy Elizabeth – International Educational Data Mining Society, 2015
The tremendous effectiveness of intelligent tutoring systems is due in large part to their interactivity. However, when learners are free to choose the extent to which they interact with a tutoring system, not all learners do so actively. This paper examines a study with a natural language tutorial dialogue system for computer science, in which…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Computer Science Education, Problem Solving
Do, Quang Xuan – ProQuest LLC, 2012
In this thesis, we study the importance of background knowledge in relation extraction systems. We not only demonstrate the benefits of leveraging background knowledge to improve the systems' performance but also propose a principled framework that allows one to effectively incorporate knowledge into statistical machine learning models for…
Descriptors: Prior Learning, Natural Language Processing, Information Retrieval, Computer Science
Becker, Lee – ProQuest LLC, 2012
While many studies have demonstrated that conversational tutoring systems have a positive effect on learning, the amount of manual effort required to author, design, and tune dialogue behaviors remains a major barrier to widespread deployment and adoption of these systems. Such dialogue systems must not only understand student speech, but must…
Descriptors: Intelligent Tutoring Systems, Speech, Computer Mediated Communication, Natural Language Processing
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Bernsen, Niels Ole; And Others – Discourse Processes, 1996
Presents principles of dialog cooperativity derived from a corpus of task-oriented spoken human-machine dialog. Analyzes the "corpus" to produce a set of dialog design principles intended to prevent users from having to initiate clarification and repair metacommunication that the system would not understand. Proposes a "more…
Descriptors: Cooperation, Discourse Analysis, Language Processing, Man Machine Systems
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