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Irum Naz; Rodney Robertson – Electronic Journal of e-Learning, 2024
This study explores the feasibility of using AI technology, specifically ChatGPT-3, to provide reliable, meaningful, and personalized feedback. Specifically, the study explores the benefits and limitations of using AI-based feedback in language learning; the pedagogical frameworks that underpin the effective use of AI-based feedback; the…
Descriptors: Artificial Intelligence, Synchronous Communication, Computer Software, Feedback (Response)
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Ozlem Uzumcu; Hasan Acilmis – Technology, Knowledge and Learning, 2024
The aim of this study is to examine the integration of AI-powered tools into the lessons in the context of the diffusion of innovation theory. One of the main features of AI-powered tools is that they provide personalized results or feedback. For this reason, it is important for students to experience these tools in person, that is, to interact…
Descriptors: Instructional Innovation, Artificial Intelligence, Teaching Methods, Computer Software
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Jia-Yin Wang; Hui-Ting Wang; Fang Yu Lin; Wen-Wen Chen – Educational Technology & Society, 2024
Developing adaptive skills poses a significant challenge for children with autism spectrum disorder (ASD). Personal hygiene, including hand-washing, was particularly important during the COVID-19 pandemic. Video self-modeling (VSM) is an effective strategy for teaching adaptive skills due to its inherent individualization nature. However, the…
Descriptors: Autism Spectrum Disorders, Students with Disabilities, Hygiene, Skill Development
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Mia S. Shaw; S. R. Toliver; Tiera Tanksley – Reading Research Quarterly, 2024
This article utilizes speculative and visual storytelling alongside interdisciplinary research on artificial intelligence (AI) and algorithmic oppression to engage in a thought experiment on how literacy studies might refuse the oppressionist logics currently undermining the possibilities of AI in literacy education. As technological advancements…
Descriptors: Digital Literacy, Literacy Education, Artificial Intelligence, Technology Uses in Education
Steven R. Frechette – ProQuest LLC, 2024
This study investigates student perceptions of artificial intelligence (AI). The study analyzed four independent variables -- age, gender, school, and employment -- to predict students' level of readiness to adopt AI within an educational setting. Using an instrument with two constructs, data was collected from a diverse, multicultural group of…
Descriptors: Community College Students, Community Colleges, Student Attitudes, Artificial Intelligence
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Noawanit Songkram; Supattraporn Upapong; Heng-Yu Ku; Narongpon Aulpaijidkul; Sarun Chattunyakit; Nutthakorn Songkram – Interactive Learning Environments, 2024
This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Teachers, Grade 1
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Margarida Lucas; Yidi Zhang; Pedro Bem-haja; Paulo Nuno Vicente – Education and Information Technologies, 2024
This study examines the relation between K-12 teachers' trust in artificial intelligence (TAI), their knowledge of AI (KAI), and their digital competence (DC). It further examines the relation between TAI and age, sex, teaching experience and International Standard Classification of Education (ISCED) levels. The study employed a comprehensive and…
Descriptors: Trust (Psychology), Teacher Attitudes, Artificial Intelligence, Technological Literacy
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Thomas Dillon – English Teaching, 2024
This study explores the integration of ChatGPT, OpenAI's conversational AI, into English as a Foreign Language (EFL) classrooms at Korean universities, focusing on student interactions and language learning strategy preferences. It categorises interactions using the Strategy Inventory for Language Learning (SILL) and Strategic Self-Regulation…
Descriptors: Literacy, Artificial Intelligence, Computer Software, Synchronous Communication
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Ndubuisi Friday Ugwu; Adewumi Segun Igbinlade; Raphael Ezamenyi Ochiaka; Ugochi Debora Ezeani; Nnaemeka Chijioke Okorie; Jacob Kehinde Opele; Toyin Segun Onayinka; Obinna Iroegbu; Ogechi Kate Onyekwere; Adijat Bolanle Adams; Precious Aigbona; Folasade Busayo Ojobola – Higher Learning Research Communications, 2024
Objective: The purpose of the study was to clarify, through the lenses of experts and frontline publishers, ethical dilemmas related to the use of artificial intelligence (AI) in research writing. Method: We conducted a rapid review of expert opinions and publishers' policy statements on ethical considerations in using AI for research writing. We…
Descriptors: Research Papers (Students), Research Reports, Academic Language, Artificial Intelligence
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Leila Mirzoyeva; Zhanna Makhanova; Mona Kamal Ibrahim; Zoya Snezhko – Cogent Education, 2024
The objective of this research is to investigate the effectiveness of integrating natural language processing (NLP) technologies into an English language learning program aimed at enhancing auditory and speaking competencies. The methodology of the research is grounded in the development and testing of the intervention effectiveness of neural…
Descriptors: Foreign Countries, Undergraduate Students, Language Skills, Auditory Training
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Steven Beyer; Frederik Grave-Gierlinger; Lars Meyer-Jenßen – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2024
Considering the widespread belief in the potential of mobile technology to enhance core activities of teachers, like lesson planning and preparation, limited research has been conducted on the use of mobile technology to support these activities. To address this research gap, this study delved into the acceptance of an intent-based chatbot…
Descriptors: Preservice Teachers, Student Attitudes, Beliefs, Users (Information)
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Verena Ruf; Yavuz Dinc; Stefan Küchemann; Markus Berndt; Steffen Steinert; Daniela Kugelmann; Jonathan Bortfeldt; Jörg Schreiber; Martin R. Fischer; Jochen Kuhn – Physical Review Physics Education Research, 2024
Graphical representations of data are common in many disciplines. Previous research has found that physics students appear to have better graph comprehension skills than students from social science disciplines, regardless of the task context. However, the graph comprehension skills of physics students have not yet been compared with (veterinary)…
Descriptors: Artificial Intelligence, Graphs, Comprehension, College Freshmen
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Yun-Fang Tu; Gwo-Jen Hwang – Interactive Learning Environments, 2024
The present study employed the draw-a-picture technique and epistemic network analysis (ENA) to reveal university students' viewpoints on ChatGPT-supported learning, as well as the conceptions, roles, and educational objectives of ChatGPT-supported learning among university students with different learning attitudes. The results showed that…
Descriptors: College Students, Student Attitudes, Knowledge Level, Artificial Intelligence
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Wei-Sheng Wang; Margus Pedaste; Chia-Ju Lin; Hsin-Yu Lee; Yueh-Min Huang; Ting-Ting Wu – Interactive Learning Environments, 2024
Virtual reality (VR) provides a unique platform for interactive learning experiences, enhancing learning, particularly in hands-on courses. However, the visual load of VR and the lack of guidance and interaction from physical teachers or peers can pose challenges for learners in self-regulated learning (SRL) and learning motivation. This study…
Descriptors: Feedback (Response), Self Management, Student Motivation, Computer Simulation
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Chathura Rajapakse; Wathsala Ariyarathna; Shanmugalingam Selvakan – ACM Transactions on Computing Education, 2024
Objectives: This article explores teacher readiness for introducing artificial intelligence (AI) into Sri Lankan schools, drawing on self-efficacy theory. Similar to some other countries, Sri Lanka plans to integrate AI into the school curriculum soon. However, a key question remains: Are teachers prepared to teach this advanced technical subject…
Descriptors: Foreign Countries, Artificial Intelligence, Teacher Attitudes, Readiness
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