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Twomey, Katherine E.; Westermann, Gert – Developmental Science, 2018
Infants are curious learners who drive their own cognitive development by imposing structure on their learning environment as they explore. Understanding the mechanisms by which infants structure their own learning is therefore critical to our understanding of development. Here we propose an explicit mechanism for intrinsically motivated…
Descriptors: Infants, Infant Behavior, Child Development, Learning Processes
Gardner, Josh; Brooks, Christopher; Li, Warren – Journal of Learning Analytics, 2018
In this paper, we evaluate the complete undergraduate co-enrollment network over a decade of education at a large American public university. We provide descriptive and exploratory analyses of the network, demonstrating that the co-enrollment networks evaluated follow power-law degree distributions similar to many other large-scale networks; that…
Descriptors: Markov Processes, Classification, Undergraduate Students, Grade Point Average
Rosa, Nicole M.; Bogart, Kathleen R.; Bonnett, Amy K.; Estill, Mariah C.; Colton, Cassandra E. – Teaching of Psychology, 2016
Historically, psychology education about disability focused narrowly on psychiatric and cognitive disabilities. Furthermore, disability tends to be viewed from the medical model, rather than the social model endorsed by disability scholars, which describes disability as primarily socially constructed. Course offerings for the psychology…
Descriptors: Undergraduate Study, Psychology, Disabilities, Course Content
Bradshaw, Laine P.; Madison, Matthew J. – International Journal of Testing, 2016
In item response theory (IRT), the invariance property states that item parameter estimates are independent of the examinee sample, and examinee ability estimates are independent of the test items. While this property has long been established and understood by the measurement community for IRT models, the same cannot be said for diagnostic…
Descriptors: Classification, Models, Simulation, Psychometrics
Karimi, Hamid; Derr, Tyler; Huang, Jiangtao; Tang, Jiliang – International Educational Data Mining Society, 2020
Online learning has attracted a large number of participants and is increasingly becoming very popular. However, the completion rates for online learning are notoriously low. Further, unlike traditional education systems, teachers, if any, are unable to comprehensively evaluate the learning gain of each student through the online learning…
Descriptors: Online Courses, Academic Achievement, Prediction, Teaching Methods
Ornelas, Fermin; Ordonez, Carlos – Technology, Knowledge and Learning, 2017
This research focuses on developing and implementing a continuous Naïve Bayesian classifier for GEAR courses at Rio Salado Community College. Previous implementation efforts of a discrete version did not predict as well, 70%, and had deployment issues. This predictive model has higher prediction, over 90%, accuracy for both at-risk and successful…
Descriptors: Community Colleges, Classification, Prediction, Models
The Consequences of the Consequences: The Impact of the Environment on People with Aphasia over Time
O'Halloran, Robyn; Carragher, Marcella; Foster, Abby – Topics in Language Disorders, 2017
Understanding the impact of the environment on the participation of people with aphasia depends on one's perspective. A long-term perspective provides a unique insight into the myriad of ways in which the environment can influence the participation of people living with aphasia over decades. In this article, the authors present the real-life story…
Descriptors: Aphasia, Speech Language Pathology, Classification, Environmental Influences
Barros, Thiago M.; Souza Neto, Plácido A.; Silva, Ivanovitch; Guedes, Luiz Affonso – Education Sciences, 2019
Predicting school dropout rates is an important issue for the smooth execution of an educational system. This problem is solved by classifying students into two classes using educational activities related statistical datasets. One of the classes must identify the students who have the tendency to persist. The other class must identify the…
Descriptors: Predictor Variables, Models, Dropout Rate, Classification
Rawson, Katherine A.; Thomas, Ruthann C.; Jacoby, Larry L. – Educational Psychology Review, 2015
Declarative concepts (i.e., key terms with short definitions of the abstract concepts denoted by those terms) are a common kind of information that students are expected to learn in many domains. A common pedagogical approach for supporting learning of declarative concepts involves presenting students with concrete examples that illustrate how the…
Descriptors: Concept Formation, Teaching Methods, Classification, Performance
Gottipati, Swapna; Shankararaman, Venky – Education and Information Technologies, 2018
The applications of learning outcomes and competency frameworks have brought better clarity to engineering programs in many universities. Several frameworks have been proposed to integrate outcomes and competencies into course design, delivery and assessment. However, in many cases, competencies are course-specific and their overall impact on the…
Descriptors: Outcomes of Education, Models, Engineering Education, Curriculum Design
Whitten, Allison; Unruh, Kathryn E.; Shafer, Robin L.; Bodfish, James W. – Journal of Autism and Developmental Disorders, 2018
Existing models of autism spectrum disorder (ASD) disagree as to whether the core features should be conceptualized as convergent (related) or divergent (unrelated), and the few previous studies addressing this question have found conflicting results. We examined standardized parent ratings of symptoms from three domains (social, communication,…
Descriptors: Autism, Symptoms (Individual Disorders), Pervasive Developmental Disorders, Genetics
Rusmana, Ai Nurlaelasari; Roshayanti, Fenny; Ha, Minsu – Asia-Pacific Science Education, 2020
Metacognitive ability is enormously important for improving students' learning performance. However, overconfidence bias may hinder students' metacognition abilities. Therefore, in this study, we conducted an intervention to reduce or debias overconfidence among students using the KAAR (knowledge, awareness, action, and reflection) model. Ninety…
Descriptors: Undergraduate Students, Metacognition, Biology, Science Education
Hatch, Deryl K.; Bohlig, E. Michael – Research in Higher Education, 2016
The definition and description of student success programs in the literature (e.g., orientation, first-year seminars, learning communities, etc.) suggest underlying programmatic similarities. Yet researchers to date typically depend on ambiguous labels to delimit studies, resulting in loosely related but separate research lines and few…
Descriptors: Community Colleges, College Students, Classification, First Year Seminars
Gibson, Andrew; Kitto, Kirsty; Bruza, Peter – Journal of Learning Analytics, 2016
Modern society demands renewed attention on the competencies required to best equip students for a dynamic and uncertain future. We present exploratory work based on the premise that metacognitive and reflective competencies are essential for this task. Bringing the concepts of metacognition and reflection together into a conceptual model within…
Descriptors: Metacognition, Reflection, Writing Assignments, Undergraduate Students
Jessurun, J. H.; Shearer, C. B.; Weggeman, M. C. D. P. – High Ability Studies, 2016
The Munich Model of Giftedness (MMG) by Heller and his colleagues, developed for the identification of gifted children, is adapted and expanded, with the aim of making it more universally usable as a model for the pathway from talents to performance. On the side of the talent-factors, the concept of multiple intelligences is introduced, and the…
Descriptors: Models, Gifted, Talent Identification, Multiple Intelligences

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