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Showing 1 to 15 of 63 results Save | Export
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Lu Ding; Sohee Kim; R. Allan Allday – Contemporary Educational Technology, 2024
With the exponential development and vast interest in artificial intelligence (AI), the global economic impact of AI is expected to reach $15.7 trillion by 2030. While AI has infiltrated everyday life, a lack of knowledge of what AI is and how AI works is ubiquitous across all ages and professions. Teaching AI literacy to non-technical individuals…
Descriptors: Artificial Intelligence, Multiple Literacies, Evaluation, Development
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Marwan Mohammad Abualrob – Contemporary Educational Technology, 2025
This study aims to uncover the prompts most frequently repeated by pre-service teachers when using the Copilot technique, as well as their reflections on its use in preparing and planning science lessons for fourth graders. The qualitative research methodology with an exploratory case-study design was conducted on a purposeful sample of 20…
Descriptors: Preservice Teachers, Artificial Intelligence, Technology Uses in Education, Grade 4
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Tommy Tanu Wijaya; Mingyu Su; Yiming Cao; Robert Weinhandl; Tony Houghton – Education and Information Technologies, 2025
Integrating AI Chatbots into teaching and learning activities is a growing trend, and understanding the readiness of preservice mathematics teachers to use AI Chatbots is crucial for successful implementation in educational settings. This study examines the factors influencing the adoption of AI Chatbots by preservice mathematics teachers in…
Descriptors: Foreign Countries, Artificial Intelligence, Educational Technology, Technology Uses in Education
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Jinglei Yu; Shengquan Yu; Ling Chen – British Journal of Educational Technology, 2025
Video-based teacher online learning enables teachers to engage in reflective practice by watching others' classroom videos, providing peer feedback (PF) and reviewing others' work. However, the quality and reliability of PF often suffer due to variations in teaching proficiency among providers, which limits its usefulness for reviewers. To improve…
Descriptors: Artificial Intelligence, Peer Evaluation, Feedback (Response), Reflection
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Sinan Hopcan; Gamze Türkmen; Elif Polat – Education and Information Technologies, 2024
With the advancement of artificial intelligence (AI) and machine learning (ML) techniques, attitudes towards these two fields have begun to gain importance in different professions. One of the affected professions is undoubtedly the teaching profession. Increasing the levels of concern for artificial intelligence and attitudes towards machine…
Descriptors: Artificial Intelligence, Educational Technology, Anxiety, Preservice Teachers
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Ozgun Uyanik Aktulun; Koray Kasapoglu; Bulent Aydogdu – Journal of Baltic Science Education, 2024
Identifying student teachers' attitudes and anxiety toward artificial intelligence (AI) in regard to their field of study might be helpful in determining whether and how AI will be employed in their future classrooms. Hence, this study aims to compare pre-service STEM and non-STEM teachers' attitudes and anxiety toward AI. In this quantitative…
Descriptors: Foreign Countries, Preservice Teachers, STEM Education, Student Attitudes
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Vafa Savaskan; Nursah Özer – Shanlax International Journal of Education, 2024
The concept of Artificial Intelligence (AI) initially emerged as a term in the field of computer science. In the subsequent years, this concept transcended its origins and became relevant across various domains of human life. Nowadays, it's possible to encounter AI in nearly every aspect of human life. In this context, it's considered noteworthy…
Descriptors: Turkish, Artificial Intelligence, Figurative Language, Preservice Teachers
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Chengming Zhang; Min Hu; Weidong Wu; Farrukh Kamran; Xining Wang – Education and Information Technologies, 2025
Artificial intelligence (AI) integration in education has grown significantly recently. However, the potential risks of AI have led to educators being wary of implementing AI systems. To discover whether AI systems can be effective in the classroom in the future, it is critical to understand how risk factors (e.g., perceived safety risks,…
Descriptors: Foreign Countries, Artificial Intelligence, Trust (Psychology), Preservice Teachers
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Ann Musgrove; Jillian Powers; Mohammad Azhar; Cristine Yao – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2024
This study examined how an online instructional module that included an unplugged robot design activity integrated computational thinking (CT), assistive technology (AT), and universal design principles into a preservice teacher education class. The research focused on how this module shaped understanding, attitudes, and comfort levels about…
Descriptors: Preservice Teacher Education, Preservice Teachers, Artificial Intelligence, Cognitive Processes
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Ho Young Yoon; Seokmin Kang; Sungyeun Kim – Journal of Computer Assisted Learning, 2024
Background: Research into enhancing the effectiveness of information delivery in asynchronous video lectures remains sparse. This study analyzes the nonverbal teaching behaviours in asynchronous online videos, drawing comparisons between pre-service and in-service teachers (ITs). Objectives: This research primarily aims to juxtapose the nonverbal…
Descriptors: Asynchronous Communication, Video Technology, Lecture Method, Nonverbal Communication
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Xian Li; Guangxin Han; Bei Fang; Juhou He – Asia-Pacific Education Researcher, 2025
The development of artificial intelligence (AI) significantly improves the effectiveness of classroom dialogue systems, but their integration into the learning environment remains challenging. To address this gap, this research presents a framework for automatic intelligent dialogue analysis, intending to promote high-quality classroom dialogue…
Descriptors: Artificial Intelligence, Classroom Communication, Discourse Analysis, Dialogs (Language)
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Lisa A. Dieker; Rebecca Hines; Ilene Wilkins; Charles Hughes; Karyn Hawkins Scott; Shaunn Smith; Kathleen Ingraham; Kamran Ali; Tiffanie Zaugg; Sachin Shah – Journal of Special Education Preparation, 2024
The options for Artificial intelligence (AI) tools used in teacher education are increasing daily, but more is only sometimes better for teachers working in already complex classroom settings. This team discusses the increase of AI in schools and provides an example from administrators, teacher educators, and computer scientists of an AI virtual…
Descriptors: Artificial Intelligence, Elementary Schools, Preservice Teachers, Preservice Teacher Education
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Krittanai Thararattanasuwan; Veena Prachagool – International Education Studies, 2024
The relevance of incorporating AI into educational settings is growing as the technology develops. This research delves into the perspective of pre-service teachers on generative AI technology. This study employed 45 pre-service teachers to raise their perspective towards AI technology and then explore its correlation about components of AI…
Descriptors: Artificial Intelligence, Educational Technology, Technology Integration, Preservice Teachers
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Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
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Shuaiyao Ma; Lei Lei – Asia Pacific Journal of Education, 2024
This study, rooted in the Technology Acceptance Model (TAM), investigates the multifaceted factors that influence teacher education students in Information-Based Teaching to embrace artificial intelligence technologies. To enrich the TAM framework, we have incorporated elements such as Artificial Intelligence Literacy (AIL), Subjective Norms (SN),…
Descriptors: Preservice Teachers, Artificial Intelligence, Technology Uses in Education, Educational Technology
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