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Backer van Ommeren, Tineke; Koot, Hans M.; Scheeren, Anke M.; Begeer, Sander – Autism: The International Journal of Research and Practice, 2017
Differences in the social limitations of girls compared to boys on the autism spectrum are still poorly understood. Impaired social-emotional reciprocity is a core diagnostic criterion for an autism spectrum disorder. This study compares sex differences in reciprocal behaviour in children with autism spectrum disorder (32 girls, 114 boys) and in…
Descriptors: Gender Differences, Child Behavior, Autism, Comparative Analysis
Ojha, Amitash; Indurkhya, Bipin; Lee, Minho – Creativity Research Journal, 2017
This pupillometry study examined the relationship between intelligence and creative cognition from the resource allocation perspective. It was hypothesized that, during a creative metaphor task, individuals with higher intelligence scores would have different resource allocation patterns than individuals with lower intelligence scores. The study…
Descriptors: Resource Allocation, Eye Movements, Creativity, Human Body
Tiekstra, Marlous; Minnaert, Alexander – Journal of Cognitive Education and Psychology, 2017
Implicit theories of intelligence play a role in teacher's actions. Adaptive instruction in and out of the classroom is important to optimize learning processes, especially in the case of at-risk students. This study explored to what extent implicit theories of intelligence play a role in the actions of educational professionals around at-risk…
Descriptors: Foreign Countries, Elementary School Students, At Risk Students, Elementary School Teachers
Bowers, Chet A. – New Directions for Adult and Continuing Education, 2017
This paper describes the key principles of an ecojustice approach to adult education. The author describes the cultural roots of the ecological crisis, the difference between ecological and individual intelligence and the linguistic colonization of the present by the past. The dangers of an overreliance on print are described and the need for a…
Descriptors: Ecology, Justice, Educational Change, Adult Education
Petkovic, Dalibor; Denic, Nebojša; Perenic, Goran – International Journal of Technology in Education and Science, 2017
Dramatic increase of learning resources has made the process of learning a timeconsuming task for learners to find relevant resources. Recommender systems are increasingly being developed in E-Learning systems to find relevant resources and facilitate both learning and teaching process. The learning style is defined as the learners' preferences in…
Descriptors: Electronic Learning, Artificial Intelligence, Cognitive Style, Taxonomy
Han Yu; Chunyan Miao; Cyril Leung; Timothy John White – npj Science of Learning, 2017
Massive Open Online Courses (MOOCs) represent a form of large-scale learning that is changing the landscape of higher education. In this paper, we offer a perspective on how advances in artificial intelligence (AI) may enhance learning and research on MOOCs. We focus on emerging AI techniques including how knowledge representation tools can enable…
Descriptors: Artificial Intelligence, MOOCs, Individualized Instruction, Psychological Patterns
Royston, R.; Oliver, C.; Moss, J.; Adams, D.; Berg, K.; Burbidge, C.; Howlin, P.; Nelson, L.; Stinton, C.; Waite, J. – Journal of Autism and Developmental Disorders, 2018
This study describes the profile of repetitive behaviour in individuals with Williams syndrome, utilising cross-syndrome comparisons with people with Prader-Willi and Down syndromes. The Repetitive Behaviour Questionnaire was administered to caregivers of adults with Williams (n = 96), Prader-Willi (n = 103) and Down (n = 78) syndromes. There were…
Descriptors: Comparative Analysis, Down Syndrome, Intelligence Quotient, Questionnaires
Bayazit, Alper; Bayram, Servet; Cumaoglu, Gonca Kizilkaya – World Journal on Educational Technology: Current Issues, 2018
Users sometimes face a common and serious problem called disorientation, which is defined as the feeling of being lost in a web-based environment. It is important to determine the reasons for disorientation in order to make the students navigate more efficiently in these environments. The aim of this study is to investigate the relationship…
Descriptors: Correlation, Cognitive Ability, Difficulty Level, Foreign Countries
Vie, Jill-Jênn; Popineau, Fabrice; Bruillard, Éric; Bourda, Yolaine – International Journal of Artificial Intelligence in Education, 2018
In large-scale assessments such as the ones encountered in MOOCs, a lot of usage data is available because of the number of learners involved. Newcomers, that just arrive on a MOOC, have various backgrounds in terms of knowledge, but the platform hardly knows anything about them. Therefore, it is crucial to elicit their knowledge fast, in order to…
Descriptors: Automation, Test Construction, Measurement, Online Courses
Majeski, Robin A.; Stover, Merrily; Valais, Teresa – Adult Learning, 2018
The community of inquiry (COI) model identifies elements which are fundamental to a successful online learning experience, namely, teaching presence, cognitive presence, and social presence. The model has received empirical support as a useful framework for understanding the online learning experience. A limitation of the model is its…
Descriptors: Emotional Response, Inquiry, Electronic Learning, Models
New England Journal of Higher Education, 2018
New England Board of Higher Education's Commission on Higher Education & Employability has thought hard over the past year about the increasing role of artificial intelligence and robotics in the future of life and work. Many others are also waking up to this landscape, which not so long ago seemed like science fiction. Machines have changed…
Descriptors: Artificial Intelligence, Robotics, Decision Making, Moral Values
Canivez, Gary L.; Dombrowski, Stefan C.; Watkins, Marley W. – Psychology in the Schools, 2018
This study examined the factor structure of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) with four standardization sample age groups (6-8, 9-11, 12-14, 15-16 years) using exploratory factor analysis (EFA), multiple factor extraction criteria, and hierarchical EFA not included in the WISC-V "Technical and Interpretation…
Descriptors: Factor Structure, Children, Intelligence Tests, Age Groups
Pezzuti, L.; Nacinovich, R.; Oggiano, S.; Bomba, M.; Ferri, R.; La Stella, A.; Rossetti, S.; Orsini, A. – Journal of Intellectual Disability Research, 2018
Background: Individuals with Down syndrome generally show a floor effect on Wechsler Scales that is manifested by flat profiles and with many or all of the weighted scores on the subtests equal to 1. Method: The main aim of the present paper is to use the statistical Hessl method and the extended statistical method of Orsini, Pezzuti and Hulbert…
Descriptors: Intelligence Tests, Children, Down Syndrome, Raw Scores
McGill, Ryan J.; Canivez, Gary L. – International Journal of School & Educational Psychology, 2018
The present study examined the factor structure of the Wechsler Intelligence Scale for Children-Fourth Edition, Spanish (WISC-IV Spanish, Wechsler, 2005a) with normative sample participants aged 6-16 years (N = 500) using confirmatory factor analytic techniques not reported in the WISC-IV Spanish Manual (Wechsler, 2005b). For the 10 core subtest…
Descriptors: Children, Intelligence Tests, Factor Analysis, Construct Validity
Pardos, Zachary A.; Dadu, Anant – Journal of Educational Data Mining, 2018
We introduce a model which combines principles from psychometric and connectionist paradigms to allow direct Q-matrix refinement via backpropagation. We call this model dAFM, based on augmentation of the original Additive Factors Model (AFM), whose calculations and constraints we show can be exactly replicated within the framework of neural…
Descriptors: Q Methodology, Psychometrics, Models, Knowledge Level

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