The aim of the current thesis was to investigate whether individuals with Autism Spectrum Disorders (ASDs) who show good visuospatial abilities, such as superior processing of local structures (Happ? & Frith, 2006; Mottron, Dawson, Souli?res, Hubert, & Burack, 2006), may also show intact or even superior learning of visuospatial information. In a series of experiments, with adolescents and adults with ASD and a comparison group of Typically Developing (TD) individuals, learning of spatial context was investigated using a visual search task, known as contextual cueing (Chun & Jiang, 1998). Contextual cueing refers to faster target detection in a visual search task with repeated exposure to a visual configuration (context), compared to configurations presented only once. Experiments 1 to 3 indicated that implicit learning may be reduced in ASD, however explicit learning was found to be preserved in ASD. In Experiments 4 to 6 implicit learning was re-examined. Results showed that when attention was oriented to the local parts of the display, individuals with ASD showed superior but atypical implicit learning of context relative to TDs (Experiment 4). However, when attention was directed to spatially distant, non-local contexts, performance was no different than for TD individuals (Experiment 5). Experiment 6 revealed superior implicit learning of local context in ASD and superior implicit learning of global context in TD individuals. Finally, Experiment 6 supported the view that contextual cueing is a local processing task, since both groups attended to local cues for longer periods of time. It is concluded that individuals with ASD show preserved or even superior implicit learning under conditions that involve attention to the local patterns.

Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.

This book presents a new way of looking at autism by considering the impact of the context in which the person lives and where interventions are delivered.--Publisher.

Autism is an emerging area of basic and clinical research, and has only recently been recognized as a major topic in biomedical research. Approximately 1 in 150 children are diagnosed as autistic, so it is also an intense growth area in behavioral and educational treatments. Financial resources have begun to be raised for more comprehensive research and an increasing number of scientists are becoming involved in autism research. In many respects, autism has become a model for conducting translational research on a psychiatric disorder. This text provides a comprehensive summary of all current knowledge related to the behavioral, experiential, and biomedical features of the autism spectrum disorders including major behavioral and cognitive syndromology, common co-morbid conditions, neuropathology, neuroimmunology, and other neurological correlates such as seizures, allergy and immunology, gastroenterology, infectious disease, and epidemiology. Edited by three leading researchers, this volume contains over 80 chapters and nine shorter commentaries by thought leaders in the field, making the book a virtual "who's who" of autism research. This carefully developed book is a comprehensive and authoritative reference for what we know in this area as well as a guidepost for the next several years in all areas of autism research.