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Pan, Yiqin; Wollack, James A. – Journal of Educational Measurement, 2021
As technologies have been improved, item preknowledge has become a common concern in the test security area. The present study proposes an unsupervised-learning-based approach to detect compromised items. The unsupervised-learning-based compromised item detection approach contains three steps: (1) classify responses of each examinee as either…
Descriptors: Test Items, Cheating, Artificial Intelligence, Identification
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Robin Griffith; Kate Davison; Lexxa Kight; Iman Stanmore – Reading Teacher, 2025
This Teaching and Learning Guide highlights how early childhood teachers can support emotional intelligence and inferential comprehension by drawing children's attention to characters' feelings and by asking students to notice evidence from the illustrations and text. During this read-aloud in Ms. Clark's first grade classroom, we see evidence of…
Descriptors: Teaching Methods, Picture Books, Preschool Teachers, Emotional Intelligence
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Maria Kasinidou; Styliani Kleanthoys; Jahna Otterbacher – Discover Education, 2025
Artificial Intelligence (AI) is now everywhere, including in the classroom. Thus, it is crucial for teachers not only to be able to use AI, but also to understand it, as they bear the responsibility of teaching the next generation with and about AI. Although there have been extensive discussions about the importance of digital skills and knowledge…
Descriptors: Foreign Countries, Technological Literacy, Teacher Attitudes, Artificial Intelligence
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Hyunsook Youn; Nancy Park; Ryan Michael Murphy – Communication Teacher, 2025
Courses: This activity can be used in writing-based (communication) courses across various disciplines including, but not limited to, introduction to writing and rhetoric, business communication, and communication research methods. Objectives: On completion of this activity, students will develop critical reading, thinking, and writing skills as…
Descriptors: Artificial Intelligence, Writing Skills, Writing Exercises, Computer Software
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Helene Ackermann; Anja Henke; Johann Chevalère; Hae Seon Yun; Verena V. Hafner; Niels Pinkwart; Rebecca Lazarides – npj Science of Learning, 2025
Rising interest in artificial intelligence in education reinforces the demand for evidence-based implementation. This study investigates how tutor agents' physical embodiment and anthropomorphism (student-reported sociability, animacy, agency, and disturbance) relate to affective (on-task enjoyment) and cognitive (task performance) learning within…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Animals, Human Body
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Xin Cui; Zhi-Qiang Ma; Xin-Ya You; Yuchen Chen; Jia-Jia Yao; Yun-Fang Tu – Educational Technology & Society, 2025
Collaborative argumentation allows groups to express, criticize, and integrate arguments to achieve the co-construction of collective knowledge. However, students often face challenges when proposing diversified arguments, gathering evidence, and rebutting others reasonably. Incorporating generative conversational agents (GCAs) into collaborative…
Descriptors: Persuasive Discourse, Rhetoric, Artificial Intelligence, Computer Uses in Education
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Sebah Al-Ali; Rob Miles – Australasian Journal of Educational Technology, 2025
There is a growing need to upskill higher education (HE) teachers for the effective and responsible integration of generative artificial intelligence (GenAI) in their classrooms. This case study sought to address this growing need by designing and delivering a training course for educators, focusing on the use of ChatGPT as it was the most…
Descriptors: Faculty Development, Artificial Intelligence, College Faculty, Technology Uses in Education
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Min Lan; Xiaofeng Zhou – npj Science of Learning, 2025
This systematic review explores the burgeoning intersection of Artificial Intelligence (AI) applications and self-regulated learning (SRL) in higher education. Aiming to synthesize empirical studies, we employed a qualitative approach to scrutinize AI's role in supporting SRL processes. Through a meticulous selection process adhering to PRISMA…
Descriptors: Artificial Intelligence, Technology Uses in Education, Self Management, College Students
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Chang Cai; Gaoxia Zhu; Min Ma – Education and Information Technologies, 2025
Interdisciplinary learning requires students to integrate knowledge and methods from different disciplines, prompting advanced skills development and knowledge construction by connecting diverse subjects. Artificial Intelligence (AI), with its rich information base and abilities to track learning and provide personalized support, has the potential…
Descriptors: Artificial Intelligence, Technology Uses in Education, Interdisciplinary Approach, Influence of Technology
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Rui Wang; Haili Ling; Jie Chen; Huijuan Fu – International Journal of Distance Education Technologies, 2025
This study adopted the Latent Dirichlet Allocation (LDA) to extract learners' needs based on 70,145 reviews from online course designed for software design and development in China and then applied Quality Function Deployment (QFD) to map learners' differentiated needs into quality attributes. Taking national first-class courses as the…
Descriptors: Educational Improvement, Student Needs, Computer Science Education, Foreign Countries
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Mostafa Al-Emran; Bassam Abu-Hijleh; AbdulRahman A. Alsewari – Education and Information Technologies, 2025
Generative Artificial Intelligence (AI) refers to advanced systems capable of creating new content by learning from vast datasets, including text, images, and code. These AI tools are increasingly being integrated into various sectors, including education, where they have the potential to enhance learning experiences. While the existing literature…
Descriptors: Artificial Intelligence, Technology Integration, Information Systems, Success
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Kaili Lu; Jianrong Zhu; Feng Pang; Rustam Shadiev – Educational Technology Research and Development, 2025
Artificial Intelligence (AI) has brought about significant changes in our lives, making AI literacy a crucial endeavor for the future. Despite its growing importance in academia, there is limited empirical research on its impact on college students' higher order thinking skills (HOTS). The present study systematically and comprehensively explores…
Descriptors: College Students, Artificial Intelligence, Digital Literacy, Thinking Skills
Yong Zhao; Ruojun Zhong – ECNU Review of Education, 2025
Purpose: The purpose of this article is to analyze educational changes, in particular transformational changes, and suggest a new approach to shift the paradigm in education using an ecological conceptual framework. Design/Approach/Methods: An ecological analysis of two key factors in education: prescribed curriculum and student autonomy.…
Descriptors: Educational Change, Holistic Approach, Personal Autonomy, Curriculum
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Angélique Létourneau; Marion Deslandes Martineau; Patrick Charland; John Alexander Karran; Jared Boasen; Pierre Majorique Léger – npj Science of Learning, 2025
The use of artificial intelligence in education (AIEd) has grown exponentially in the last decade, particularly intelligent tutoring systems (ITSs). Despite the increased use of ITSs and their promise to improve learning, their real educational value remains unclear. This systematic review aims to identify the effects of ITSs on K-12 students'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Intelligent Tutoring Systems, Elementary Secondary Education
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Peter Bannister; Mark Carver – Professional Development in Education, 2025
Responding to GenAI technologies, academics press for PLD that informs pedagogical practice and policy development. However, insufficient critical evaluation of whose knowledge informs this and its underlying complexity has resulted in excessively reductive offerings that either champion specific tools or advocate for their prohibition. Engaging…
Descriptors: Artificial Intelligence, Faculty Development, English for Academic Purposes, Language Teachers
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