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João Vitor L. B. Nascimento; Jário José Santos; Ig Ibert Bittencourt – International Journal of Artificial Intelligence in Education, 2025
The advancement of technology in education has transformed traditional classrooms into virtual learning environments yet concerns persist about how these technologies may inadvertently perpetuate racial stereotypes. Our study employed a 2 × 2 factorial design, with the first factor being the race of participants (Black, White) and the second…
Descriptors: Racism, Ethnic Stereotypes, Profiles, Anxiety
Xiaohu Xie; Tao Wang – Education and Information Technologies, 2024
Technological progress has a significant impact on higher education and increases the popularity of artificial intelligence technologies in universities of different countries. This research was based at Tianshui Normal University in China. The authors examined the impact of an interactive learning environment based on artificial intelligence in…
Descriptors: Artificial Intelligence, Technology Uses in Education, Influence of Technology, Foreign Countries
Joseph C. Y. Lau; Emily Landau; Qingcheng Zeng; Ruichun Zhang; Stephanie Crawford; Rob Voigt; Molly Losh – Autism: The International Journal of Research and Practice, 2025
Many individuals with autism experience challenges using language in social contexts (i.e., pragmatic language). Characterizing and understanding pragmatic variability is important to inform intervention strategies and the etiology of communication challenges in autism; however, current manual coding-based methods are often time and labor…
Descriptors: Artificial Intelligence, Models, Pragmatics, Language Variation
Zhang, Weiwen – Online Submission, 2020
Recently Prof. Howard Gardner, an outstanding psychologist in the worldwide accepted the interview from Dr. Weiwen Zhang, and talked about a wide range of MI theory and relevant fields, which mainly involved in its core ideas, current situation and future development, and also involved its application in some current hot issues, which gave us…
Descriptors: Multiple Intelligences, Learning Theories, Misconceptions, Criticism
Musso, Mariel F.; Cómbita, Lina M.; Cascallar, Eduardo C.; Rueda, M. Rosario – Mind, Brain, and Education, 2022
The objective of this research was to develop robust predictive models of the gains in working memory (WM) and fluid intelligence (Gf) following executive attention training in children, using genetic markers, gender, and age variables. We explore the influence of genetic variables on individual differences in susceptibility to intervention.…
Descriptors: Genetics, Artificial Intelligence, Gender Differences, Age Differences
OECD Publishing, 2021
Artificial intelligence (AI) and robotics are major breakthrough technologies that are transforming the economy and society. The OECD's Artificial Intelligence and the Future of Skills (AIFS) project is developing a programme to assess the capabilities of AI and robotics, and their impact on education and work. This volume reports on the first…
Descriptors: Artificial Intelligence, Skill Development, Evaluation, Competence
Rennie, Joseph P.; Zhang, Mengya; Hawkins, Erin; Bathelt, Joe; Astle, Duncan E. – Developmental Science, 2020
We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working memory (WM) training. We used self-organizing maps (SOMs)--a type of simple artificial neural network--to represent multivariate cognitive training data, and then tested whether the way tasks are…
Descriptors: Short Term Memory, Teaching Methods, Artificial Intelligence, Cognitive Development
Erbeli, Florina; He, Kai; Cheek, Connor; Rice, Marianne; Qian, Xiaoning – Scientific Studies of Reading, 2023
Purpose: Researchers have developed a constellation model of decodingrelated reading disabilities (RD) to improve the RD risk determination. The model's hallmark is its inclusion of various RD indicators to determine RD risk. Classification methods such as logistic regression (LR) might be one way to determine RD risk within the constellation…
Descriptors: At Risk Students, Reading Difficulties, Classification, Comparative Analysis
Schneider, W. Joel; Kaufman, Alan S. – International Journal of School & Educational Psychology, 2016
As documented in this special issue, all over the world hard choices must be made in education, government, business, and medicine. Intelligence tests, used intelligently and with appropriate ethical safeguards, are one tool of many that help make hard choices work out well, or at least better than the next-best alternative (Kaufman, Raiford,…
Descriptors: Intelligence Quotient, Artificial Intelligence, Children, Adolescents
Astle, Duncan E.; Bathelt, Joe; Holmes, Joni – Developmental Science, 2019
Our understanding of learning difficulties largely comes from children with specific diagnoses or individuals selected from community/clinical samples according to strict inclusion criteria. Applying strict exclusionary criteria overemphasizes within group homogeneity and between group differences, and fails to capture comorbidity. Here, we…
Descriptors: Cognitive Mapping, Learning Problems, Comorbidity, Identification
Spektor-Precel, Karen; Mioduser, David – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2015
Nowadays, we are surrounded by artifacts that are capable of adaptive behavior, such as electric pots, boiler timers, automatic doors, and robots. The literature concerning human beings' conceptions of "traditional" artifacts is vast, however, little is known about our conceptions of behaving artifacts, nor of the influence of the…
Descriptors: Foreign Countries, Young Children, Theory of Mind, Behavior
Dowe, David L.; Hernandez-Orallo, Jose – Intelligence, 2012
Complex, but specific, tasks--such as chess or "Jeopardy!"--are popularly seen as milestones for artificial intelligence (AI). However, they are not appropriate for evaluating the intelligence of machines or measuring the progress in AI. Aware of this delusion, Detterman has recently raised a challenge prompting AI researchers to evaluate their…
Descriptors: Intelligence Tests, Intelligence Quotient, Artificial Intelligence, Measurement
Embretson, Susan E. – Measurement: Interdisciplinary Research and Perspectives, 2004
The last century was marked by dazzling changes in many areas, such as technology and communications. Predictions into the second century of testing are seemingly difficult in such a context. Yet, looking back to the turn of the last century, Kirkpatrick (1900), in his American Psychological Association presidential address, presented fundamental…
Descriptors: Ability, Testing, Futures (of Society), Psychometrics

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