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Lei Du; Beibei Lv – Education and Information Technologies, 2024
This research examines the influence of integrating generative artificial intelligence (GAI) in education, focusing on its acceptance and utilization among elementary education students. Grounded in the Task-Technology Fit (TTF) Theory and an expanded iteration of the Unified Theory of Acceptance and Use of Technology (UTAUT) model, the study…
Descriptors: Influences, Student Attitudes, Artificial Intelligence, Technology Uses in Education
Unggi Lee; Yeil Jeong; Junbo Koh; Gyuri Byun; Yunseo Lee; Youngsun Hwang; Hyeoncheol Kim; Cheolil Lim – Educational Technology & Society, 2024
Debate is a universally acknowledged competency for its vital role in fostering essential skills such as analytical reasoning, eloquent communication, and persuasive argument construction. This is relevant in both formal educational settings like classrooms and informal venues such as after-school clubs. Traditional debate training methods often…
Descriptors: Artificial Intelligence, Debate, Computer Oriented Programs, Technology Uses in Education
James Ewert Duah; Paul McGivern – International Journal of Information and Learning Technology, 2024
Purpose: This study examines the impact of generative artificial intelligence (GenAI), particularly ChatGPT, on higher education (HE). The ease with which content can be generated using GenAI has raised concerns across academia regarding its role in academic contexts, particularly regarding summative assessments. This research makes a unique…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Lee McCallum – Journal for Multicultural Education, 2024
Purpose: This paper aims to present a lesson that showcases how artificial intelligence (AI) tools may be chiefly used in L2 language classrooms to design culture-focussed telecollaboration tasks and aid their completion by students. Design/methodology/approach: The paper begins by reviewing traditional approaches and guidance for developing…
Descriptors: Artificial Intelligence, Intercultural Communication, Second Language Learning, Telecommunications
Marcel Mierwald – Journal of Educational Media, Memory and Society, 2024
Generative artificial intelligence (AI) offers new opportunities for history education, such as the ability to chat with historical figures. However, little is known about pupils' interaction with AI applications such as ChatGPT. A qualitative case study was conducted to explore how pupils (n = 21, year nine, fourteen years old) interacted with…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, History Instruction
Pedro Isaias, Editor; Demetrios G. Sampson, Editor; Dirk Ifenthaler, Editor – Cognition and Exploratory Learning in the Digital Age, 2024
The Cognition and Exploratory Learning in the Digital Age (CELDA) conference focuses on discussing and addressing the challenges pertaining to the evolution of the learning process, the role of pedagogical approaches and the progress of technological innovation, in the context of the digital age. In each edition, CELDA, gathers researchers and…
Descriptors: Artificial Intelligence, Cognitive Processes, Discovery Learning, Teaching Methods
Raj Sandu; Ergun Gide; Mahmoud Elkhodr – Discover Education, 2024
Artificial intelligence (AI) tools, notably ChatGPT, are increasingly recognised for their transformative potential in higher education. This study employs a detailed case study approach complemented by a survey, delving into ChatGPT's impact on pedagogical practices, student engagement, and academic performance. It involved 74 undergraduate and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Foreign Countries
Dorottya Demszky; Jing Liu; Heather C. Hill; Dan Jurafsky; Chris Piech – Educational Evaluation and Policy Analysis, 2024
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage…
Descriptors: Online Courses, Automation, Feedback (Response), Large Group Instruction
Barokova, Mihaela; Tager-Flusberg, Helen – Journal of Autism and Developmental Disorders, 2020
The role of language in autism spectrum disorder (ASD), more specifically, its function in social communication and strong predictive power on future outcomes, warrants language assessments that have good psychometric properties that capture the heterogeneity of language ability found among diagnosed individuals. Given the rapid growth in…
Descriptors: Autism, Pervasive Developmental Disorders, Natural Language Processing, Outcome Measures
Williams, John N. – Language Learning, 2020
Over the past decades, research employing artificial grammar, sequence learning, and statistical learning paradigms has flourished, not least because these methods appear to offer a window, albeit with a restricted view, on implicit learning processes underlying natural language learning. But these paradigms usually provide relatively little…
Descriptors: Learning Processes, Grammar, Sequential Learning, Natural Language Processing
Dascalu, Marina-Dorinela; Ruseti, Stefan; Dascalu, Mihai; McNamara, Danielle; Trausan-Matu, Stefan – Grantee Submission, 2020
Reading comprehension requires readers to connect ideas within and across texts to produce a coherent mental representation. One important factor in that complex process regards the cohesion of the document(s). Here, we tackle the challenge of providing researchers and practitioners with a tool to visualize text cohesion both within (intra) and…
Descriptors: Network Analysis, Graphs, Connected Discourse, Reading Comprehension
Allard, Danièle; Mizoguchi, Riichiro – Research and Practice in Technology Enhanced Learning, 2021
This article introduces a novel, holistic framework--named Dr. Mosaik--that encompasses explanations of the entire tense-aspect system, while highlighting eight comprehensive rules that explain the main workings of the system. In turn, this provides a limited number of "anchor points" on which to time-efficiently address instruction and…
Descriptors: Intensive Language Courses, English, Morphemes, Form Classes (Languages)
Albertson, Brendon – Research-publishing.net, 2021
A Computer-Assisted Language Learning (CALL) application, TextMix, was developed as a proof-of-concept for applying Natural Language Processing (NLP) sentence chunking techniques to creating 'sentence scramble' learning tasks. TextMix addresses limitations of existing applications for creating sentence scrambles by using NLP to parse and scramble…
Descriptors: Computer Assisted Instruction, Second Language Learning, Natural Language Processing, Sentences
Florian Hesse; Gerrit Helm – Journal of Digital Learning in Teacher Education, 2025
AI is changing the way writing is learnt at university and taught in schools. Different institutions hence call for integrating programs on writing with AI in teacher education. These must be based on the needs of the participants, which are, however, still unexplored. This article fills this gap with findings from a February 2024 questionnaire…
Descriptors: Artificial Intelligence, Technology Uses in Education, Writing (Composition), Preservice Teacher Education
Mary Rice; Nicholas DePascal; Joaquín T. Argüello de Jesús; Helen McFeely; Amy Traylor; Lehman Heaviland – Professional Development in Education, 2025
With the introduction of artificial intelligence (AI), particularly Generative AI (GenAI) to school settings, teachers are likely to be drawn into professional learning scenarios where they will be expected to learn how to use programs and applications for remediation and tutoring of children. Previous research highlights how professional learning…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education

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