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Tulsi A. Radhoe; Joost A. Agelink van Rentergem; Carolien Torenvliet; Annabeth P. Groenman; Wikke J. van der Putten; Hilde M. Geurts – Journal of Autism and Developmental Disorders, 2024
Autism is heterogeneous, which complicates providing tailored support and future prospects. We aim to identify subgroups in autistic adults with average to high intelligence, to clarify if certain subgroups might need support. We included 14 questionnaire variables related to aging and/or autism (e.g., demographic, psychological, and lifestyle).…
Descriptors: Adults, Autism Spectrum Disorders, Population Groups, Intelligence
Beena Joseph; Sajimon Abraham – Knowledge Management & E-Learning, 2023
Currently, the majority of e-learning lessons created and disseminated advocate a "one-size-fits-all" teaching philosophy. The e-learning environment, however, includes slow learners in a noticeable way, just like in traditional classroom settings. Learning analytics of educational data from a learning management system (LMS) have been…
Descriptors: Electronic Learning, Learning Management Systems, Slow Learners, Educational Environment
Zheng, Shuting – ProQuest LLC, 2018
Children with autism spectrum disorder (ASD) show a wide range of developmental characteristics and differ from each other in terms of symptom presentation. This heterogeneity leads to difficulties when trying to individualize treatments that work for individual children with ASD. Therefore, identifying and understanding subgroups of children on…
Descriptors: Preschool Children, Autism, Pervasive Developmental Disorders, Cluster Grouping
Elphinstone, Brad; Tinker, Sean – Journal of College Student Development, 2017
The Motivation and Engagement Scale-University/College (MES-UC) was used to identify student typologies on the basis of adaptive and maladaptive academic cognitions and behaviours. The sample comprised first-year (n = 390), second-year (n = 300), and third-year (n = 251) undergraduate students with 4 student typologies identified: high…
Descriptors: Student Motivation, Undergraduate Students, Likert Scales, Cohort Analysis
Keil, Frank C.; Stein, Courtney; Webb, Lisa; Billings, Van Dyke; Rozenblit, Leonid – Cognitive Science, 2008
The division of cognitive labor is fundamental to all cultures. Adults have a strong sense of how knowledge is clustered in the world around them and use that sense to access additional information, defer to relevant experts, and ground their own incomplete understandings. One prominent way of clustering knowledge is by disciplines similar to…
Descriptors: Social Sciences, Young Children, Cognitive Development, Cluster Grouping