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Dale, Brittany A.; Finch, William Holmes; Shellabarger, Kassie A. R. – Psychology in the Schools, 2023
Ancillary index scales provide assessment professionals the opportunity to conduct a more comprehensive interpretation of a student's performance on the Wechsler Intelligence Scales for Children, Fifth Edition (WISC-V); however, little is known about the performance of children with autism spectrum disorder (ASD) on these scales. The ASD special…
Descriptors: Children, Intelligence Tests, Autism Spectrum Disorders, Performance
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Giangrande, Evan J.; Beam, Christopher R.; Finkel, Deborah; Davis, Deborah W.; Turkheimer, Eric – Child Development, 2022
This study investigated the systematic rise in cognitive ability scores over generations, known as the "Flynn Effect," across middle childhood and early adolescence (7-15 years; 291 monozygotic pairs, 298 dizygotic pairs; 89% White). Leveraging the unique structure of the Louisville Twin Study (longitudinal data collected continuously…
Descriptors: Cognitive Ability, Scores, Intelligence Tests, Children
Guerin, Julia M. – ProQuest LLC, 2022
Background: Children with reading difficulty exhibit deficits in multiple cognitive areas (e.g., language skills, working memory, processing speed). Therefore, evaluation of reading difficulty typically includes assessment of both academic functioning and general intelligence (IQ). Although the IQ construct is considered robust in the general…
Descriptors: Intelligence, Intelligence Tests, Children, Reading Difficulties
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Romy Gonçalves; Romy Gaillard; Kelly K. Ferguson; Sara Sammallahti; Manon H. Hillegers; Eric A. P. Steegers; Hanan El Marroun; Vincent W. V. Jaddoe – JCPP Advances, 2025
Background: Fetal life and infancy might be critical periods for brain development leading to increased risks of neurocognitive disorders and psychopathology later in life. We examined the associations of fetal and infant weight growth patterns and birth characteristics with behavior and cognitive outcomes at the age of 13 years. Methods:…
Descriptors: Birth, Infants, Body Weight, Child Development
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Yen-Chin Wang; Chung-Yuan Cheng; Chi-Shin Wu; Chi-Chun Lee; Susan Shur-Fen Gau – Autism: The International Journal of Research and Practice, 2025
Machine-learning models can assist in diagnosing autism but have biases. We examines the correlates of misclassifications and how training data affect model generalizability. The Social Responsive Scale data were collected from two cohorts in Taiwan: the clinical cohort comprised 1203 autistic participants and 1182 non-autistic comparisons, and…
Descriptors: Artificial Intelligence, Autism Spectrum Disorders, Clinical Diagnosis, Error Patterns
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Halpern, Diane F.; Dunn, Dana S. – Journal of Intelligence, 2021
Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, or confirmation…
Descriptors: Critical Thinking, Intelligence, Problem Solving, Intelligence Quotient
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Horwitz, Ernst; Vos, Melissa; De Bildt, Annelies; Greaves-Lord, Kirstin; Rommelse, Nanda; Schoevers, Robert; Hartman, Catharina – Autism: The International Journal of Research and Practice, 2023
There is an ongoing debate as to whether autism spectrum disorder (ASD) is expressed differently in women than men. It is unclear whether differences found are specific to autism or merely reflecting normative development. In this study, we compared sex differences in developmental trajectories of autistic and co-occurring psychopathological…
Descriptors: Gender Differences, Autism Spectrum Disorders, Comorbidity, Psychopathology
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Gulzhanar Arynova; Gulnar Uaisova; Aigul Zhumadullayeva; Sholpan Kalbergenova; Maryam Bekbaeva – Journal of Education and e-Learning Research, 2023
The development of social intelligence is a delicate issue among teenagers. Insufficient social intelligence leads to social disorientation which may impede students' capacity to grow positively and to understand the reasons for their actions and the logic of the development of complex situations of interpersonal interaction. This study aims to…
Descriptors: Influence of Technology, Technology Uses in Education, Interpersonal Competence, Intelligence
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Zhou, Todd; Jiao, Hong – Educational and Psychological Measurement, 2023
Cheating detection in large-scale assessment received considerable attention in the extant literature. However, none of the previous studies in this line of research investigated the stacking ensemble machine learning algorithm for cheating detection. Furthermore, no study addressed the issue of class imbalance using resampling. This study…
Descriptors: Cheating, Measurement, Artificial Intelligence, Algorithms
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Paige Haber-Curran; Erin Williamson – New Directions for Student Leadership, 2023
This article focuses on integrating topics of emotional intelligence in curricular and co-curricular collegiate leadership education. The authors spotlight one institution's use of emotionally intelligent leadership as a framework across a variety of leadership programs, courses, and trainings. Critiques, considerations, and resources to inform…
Descriptors: Emotional Intelligence, Leadership Training, College Students, Courses
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Junfeng Man; Rongke Zeng; Xiangyang He; Hua Jiang – Knowledge Management & E-Learning, 2024
At present, the widespread use of online education platforms has attracted the attention of more and more people. The application of AI technology in online education platform makes multidimensional evaluation of students' ability become the trend of intelligent education in the future. Currently, most existing studies are based on traditional…
Descriptors: Cognitive Ability, Student Evaluation, Algorithms, Learning Processes
Adeolu Tolu Ebenezer Oyebode – ProQuest LLC, 2024
The COVID-19 pandemic led to an increase in Online learning. With this increase comes several challenges for instructors and students such as connectivity issues and student engagement. Organizations are spending millions of dollars developing emerging technologies such as emotion AI and other AI applications without taking cognizance of users'…
Descriptors: Teaching Methods, Synchronous Communication, Electronic Learning, Emotional Intelligence
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Yi Zheng; Steven Nydick; Sijia Huang; Susu Zhang – Educational Measurement: Issues and Practice, 2024
The recent surge of machine learning (ML) has impacted many disciplines, including educational and psychological measurement (hereafter shortened as "measurement"). The measurement literature has seen rapid growth in applications of ML to solve measurement problems. However, as we emphasize in this article, it is imperative to critically…
Descriptors: Artificial Intelligence, Measurement, Measurement Equipment, Psychological Evaluation
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Lisa Ruth Brunner; Wei William Tao – Journal of International Students, 2024
Artificial intelligence (AI) and automation are newly impacting the governance of international students, a temporary resident category significant for both direct economic contributions and the formation of a "pool" of potential future immigrants in many immigrant-dependent countries. This paper focuses on tensions within Canada's…
Descriptors: Artificial Intelligence, Automation, Migration, Foreign Students
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Nicholas Smith; Darby Vickers – Theory and Research in Education, 2024
Artificial intelligence technologies have become a ubiquitous part of human life. This prompts us to ask, "how should we live well with artificial intelligence?" Currently, the most prominent candidate answers to this question are principlist. According to these approaches, if you teach people some finite set of principles or convince…
Descriptors: Artificial Intelligence, Moral Values, Ethics, Philosophy
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