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Christian Basil Omeh; Chijioke Jonathan Olelewe; Xiao Hu – Education and Information Technologies, 2025
The adoption of generative AI in educational process carries both potential advantages and risks hence there is a need for ethical principles to guide its adoption in education. A population of 443 TVET educators, including 325 male and 118 female, was selected for this study using a mixed research design from the seven TVET public institutions in…
Descriptors: Artificial Intelligence, Technology Uses in Education, Career and Technical Education, Ethics
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Liliana Yadira Yela-Pantoja; Martha Leticia Gaeta González; Juan Carlos Luis-Pascual – Electronic Journal of Research in Educational Psychology, 2025
As the basis for developing emotional intelligence, emotional education is fundamental to the development of students as integrated individuals and their ability to coexist harmoniously with other people over time. Teachers must therefore receive emotional education. However, the range of measures to provide such education in Latin America in…
Descriptors: Emotional Intelligence, Emotional Development, Teacher Competencies, Well Being
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Rizwaan Malik; Dorna Abdi; Rose Wang; Dorottya Demszky – British Journal of Educational Technology, 2025
Despite well-designed curriculum materials, teachers often face challenges implementing them due to diverse classroom needs. This paper investigates whether large language models (LLMs) can support middle school math teachers by helping create high-quality curriculum scaffolds, which we define as the adaptations and supplements teachers employ to…
Descriptors: Curriculum Design, Instructional Materials, Artificial Intelligence, Curriculum Implementation
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Priya Saha; Md. Shakhawat Hossain; Nirmal Chandra Roy; Abdullah Al Masud; Ruhul Amin – On the Horizon, 2025
Purpose: This study aims to evaluate students' intention and actual use (AU) of artificial intelligence (AI) tools' to discover how the power of AI influences learning and academic success. Design/methodology/approach: This paper used the unified theory of acceptance and use of technology (UTAUT) to develop a structural equation model (SEM) and…
Descriptors: Artificial Intelligence, Technology Uses in Education, Intention, Student Behavior
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Guher Gorgun; Okan Bulut – Educational Measurement: Issues and Practice, 2025
Automatic item generation may supply many items instantly and efficiently to assessment and learning environments. Yet, the evaluation of item quality persists to be a bottleneck for deploying generated items in learning and assessment settings. In this study, we investigated the utility of using large-language models, specifically Llama 3-8B, for…
Descriptors: Artificial Intelligence, Quality Control, Technology Uses in Education, Automation
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Ryan Hare; Sarah Ferguson; Ying Tang – British Journal of Educational Technology, 2025
With increasing interest in computer-assisted education, AI-integrated systems become highly applicable with their ability to adapt based on user interactions. In this context, this paper focuses on understanding and analysing first-year undergraduate student responses to an intelligent educational system that applies multi-agent reinforcement…
Descriptors: Student Experience, Educational Games, Design, Learning Experience
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Florian Weber; Thiemo Wambsganss; Matthias Söllner – British Journal of Educational Technology, 2025
Recent developments in artificial intelligence (AI) have significantly influenced educational technologies, reshaping the teaching and learning landscape. However, the notion of fully automating the teaching process remains contentious. This paper explores the concept of hybrid intelligence (HI), which emphasizes the synergistic collaboration…
Descriptors: Legal Education (Professions), Writing Skills, Skill Development, Feedback (Response)
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Sghaier Guizani; Tehseen Mazhar; Tariq Shahzad; Wasim Ahmad; Afsha Bibi; Habib Hamam – Discover Education, 2025
Artificial intelligence-driven Chatbots, especially large language models (LLMs) like GPT-4, represent significant progress in digital education. These models excel in mimicking human-like text and transforming learning and teaching methods. This study examines the development, application, and impact of LLMs in education. It highlights their role…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
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André Coy; Phaedra S. Mohammed; Paulson Skerrit – International Journal of Artificial Intelligence in Education, 2025
Deaf learners in the Global South struggle to access equitable education, in particular, there are few instances where they can be facilitated in inclusive classrooms. The challenges include a lack of teachers that can sign proficiently, the unavailability of interpreters and few teachers trained in Deaf education. This paper explores the…
Descriptors: Deafness, Students with Disabilities, Equal Education, Access to Education
Emmanuel Dumbuya – Online Submission, 2025
The integration of artificial intelligence (AI) into educational ecosystems represents a paradigm shift in pedagogical practices and educational governance. While AI offers unprecedented opportunities to personalize learning, optimize administrative processes, and provide intelligent tutoring, it poses significant challenges to maintaining human…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Technology Integration
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Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
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Matthew Landers – Higher Education for the Future, 2025
This article presents a brief overview of the state-of-the-art in large language models (LLMs) like ChatGPT and discusses the difficulties that these technologies create for educators with regard to assessment. Making use of the 'arms race' metaphor, this article argues that there are no simple solutions to the 'AI problem'. Rather, this author…
Descriptors: Ethics, Cheating, Plagiarism, Artificial Intelligence
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Aidan Doyle; Pragnya Sridhar; Arav Agarwal; Jaromir Savelka; Majd Sakr – Journal of Computer Assisted Learning, 2025
Background: In computing education, educators are constantly faced with the challenge of developing new curricula, including learning objectives (LOs), while ensuring that existing courses remain relevant. Large language models (LLMs) were shown to successfully generate a wide spectrum of natural language artefacts in computing education.…
Descriptors: Computer Science Education, Artificial Intelligence, Learning Objectives, Curriculum Development
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Wen Xin Zhang; John J. H. Lin; Ying-Shao Hsu – Journal of Computer Assisted Learning, 2025
Background Study: Assessing learners' inquiry-based skills is challenging as social, political, and technological dimensions must be considered. The advanced development of artificial intelligence (AI) makes it possible to address these challenges and shape the next generation of science education. Objectives: The present study evaluated the SSI…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Inquiry, Active Learning
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Qiuyi Kong; Harry Fraser; Felicia Crysta Elwina; Ted Ruffman – International Journal of Behavioral Development, 2025
The present study provided a novel examination of how children's theory of mind (ToM) might be related to two maternal beliefs: (1) social dominance orientation (SDO: the belief that inequalities in society are justified) and (2) right-wing authoritarianism (RWA: a belief in following established authorities). We reasoned that these beliefs could…
Descriptors: Foreign Countries, Preschool Children, Theory of Mind, Mothers
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