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Bridget Letuzinger; Derek B. Rodgers; Mackenzie E. Savaiano – Education and Training in Autism and Developmental Disabilities, 2024
The current study examined the effectiveness of a reading curriculum of explicit instruction on the letter-sound knowledge of a sample of elementary-aged students with Down syndrome. The procedures were adapted from prior research (King et al., 2020; Lemons et al., 2018; Lemons et al., 2015). Three participants between 9 and 11 years old…
Descriptors: Phonics, Spelling Instruction, Down Syndrome, Intervention
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Robison, Matthew K.; Brewer, Gene A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2022
The present study examined individual differences in 3 cognitive abilities: attention control (AC), working memory capacity (WMC), and fluid intelligence (gF) as they relate the tendency to experience task-unrelated thoughts (TUTs) and the regulation of arousal. Cognitive abilities were measured with a battery of 9 laboratory tasks, TUTs were…
Descriptors: Individual Differences, Short Term Memory, Attention Control, Intelligence
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Martschenko, Daphne Oluwaseun – Critical Studies in Education, 2023
This paper utilizes the concept of 'discriminate biopower' to explore how advancements in social and behavioral genomics might inform the racially exclusionary nature of one of the most inequitable and academically coveted environments in American public education: gifted education. In its birth, gifted education became a mechanism for regulating…
Descriptors: Academically Gifted, Gifted Education, Genetics, Equal Education
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Schmank, Christopher J.; Goring, Sara Anne; Kovacs, Kristof; Conway, Andrew R. A. – Journal of Intelligence, 2021
In a recent publication in the Journal of Intelligence, Dennis McFarland mischaracterized previous research using latent variable and psychometric network modeling to investigate the structure of intelligence. Misconceptions presented by McFarland are identified and discussed. We reiterate and clarify the goal of our previous research on network…
Descriptors: Intelligence, Psychometrics, Cognitive Structures, Structural Equation Models
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Meng, Huijuan; Ma, Ye – Educational Measurement: Issues and Practice, 2023
In recent years, machine learning (ML) techniques have received more attention in detecting aberrant test-taking behaviors due to advantages when compared to traditional data forensics methods. However, defining "True Test Cheaters" is challenging--different than other fraud detection tasks such as flagging forged bank checks or credit…
Descriptors: Artificial Intelligence, Cheating, Testing, Information Technology
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Hsu, Yu-Chang; Ching, Yu-Hui – TechTrends: Linking Research and Practice to Improve Learning, 2023
Generative artificial intelligence (GenAI), such as ChatGPT, has taken the world by storm. ChatGPT attracted 1 million users in 5 days and 100 million users in 2 months since its launch in November 2022. In this first article of a two-part series, we discuss the overall dynamic frontier of GenAI, its potential uses and benefits in education,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Benefits
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Birks, Daniel; Clare, Joseph – International Journal for Educational Integrity, 2023
This paper connects the problem of artificial intelligence (AI)-facilitated academic misconduct with crime-prevention based recommendations about the prevention of academic misconduct in more traditional forms. Given that academic misconduct is not a new phenomenon, there are lessons to learn from established information relating to misconduct…
Descriptors: Artificial Intelligence, Cheating, Student Behavior, Prevention
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Florent Vinchon; Todd Lubart; Sabrina Bartolotta; Valentin Gironnay; Marion Botella; Samira Bourgeois-Bougrine; Jean-Marie Burkhardt; Nathalie Bonnardel; Giovanni Emanuele Corazza; Vlad Glaveanu; Michael Hanchett Hanson; Zorana Ivcevic; Maciej Karwowski; James C. Kaufman; Takeshi Okada; Roni Reiter-Palmon; Andrea Gaggioli – Journal of Creative Behavior, 2023
With the advent of artificial intelligence (AI), the field of creativity faces new opportunities and challenges. This manifesto explores several scenarios of human--machine collaboration on creative tasks and proposes "fundamental laws of generative AI" to reinforce the responsible and ethical use of AI in the creativity field. Four…
Descriptors: Artificial Intelligence, Creativity, Man Machine Systems, Ethics
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Tianjiao Wang; Xiaona Xia – SAGE Open, 2023
The study of learning behaviors with multi features is of great significance for interactive cooperation. The data prediction and decision are to realize the comprehensive analysis and value mining. In this study, hierarchical learning behavior based on feature cluster is proposed. Based on the massive data in interactive learning environment, the…
Descriptors: Cluster Grouping, Mathematical Models, Artificial Intelligence, Learning Analytics
Lehong Shi – ProQuest LLC, 2023
Artificial intelligence (AI), utilizing machine learning techniques to 'learn' from data, as humans learn from experiences, has the promise to perform various cognitive tasks, such as learning, thinking, problem-solving, and decision-making, which usually demands human cognition. In recent decades, the remarkable advancements in AI have led to its…
Descriptors: Artificial Intelligence, Educational Technology, Teaching Methods, Teacher Role
Pierrette Renee Dagg – ProQuest LLC, 2023
Software powered by artificial intelligence (AI) is used widely in the United States in education as a tool for teaching, administration, student assessment, and other purposes. Curriculum delivery, tutoring, support for students with disabilities and resource allocations are some of the applications of the technology. The normative, ideological,…
Descriptors: Artificial Intelligence, Ethics, Philosophy, Technology Uses in Education
Emmanuel Dumbuya – Online Submission, 2025
Artificial Intelligence (AI) is revolutionizing industries, yet its integration into education remains underutilized. This paper advocates for embedding AI tools in curriculum design to personalize learning experiences, address diverse student needs, and equip learners with future-ready skills. By leveraging AI's capabilities, educators can create…
Descriptors: Artificial Intelligence, Curriculum Design, Individualized Instruction, Technology Uses in Education
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Ishrat Ahmed; Paul Alvarado; Siddharth Jain; Tracy Arner; Elizabeth Reilley; Danielle S. McNamara – Grantee Submission, 2025
The rapid evolution of artificial intelligence (AI) has created an unprecedented opportunity for innovation across industries, but its complexity often presents a steep learning curve for many (Roberts & Candi, 2024; Gunner, 2025). This highlights the need for user-friendly tools that bridge the gap between AI's potential and its practical…
Descriptors: State Universities, Artificial Intelligence, Usability, Innovation
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Figen Egin; Aytug Onan; Hatice Yildiz Durak – European Journal of Education, 2025
This study examines pre-service teachers' understanding of technology integration and the role of AI tools in shaping this perspective. Open-ended responses, analysed using topic modelling, reveal the main themes in pre-service teachers' views and compare them with topics generated by AI tools like ChatGPT, Gemini, and Bing AI. Key themes in…
Descriptors: Educational Technology, Preservice Teachers, Artificial Intelligence, Teacher Attitudes
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Jamal Eddine Rafiq; Abdelwahed Namir; Abdelali Zakrani; Mohammed Amraouy; Abdellah Bennane – Journal of Educators Online, 2025
This study examines the evolution of educational practices in the digital era and the integration of information technologies in teaching. Through an automated search in six digital libraries, we identified 99 relevant studies spanning the period from 1990 to 2021. We draw on a systematic mapping approach to classify these studies for better…
Descriptors: Educational Development, Educational Practices, Information Technology, Artificial Intelligence
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