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A Quantisation of Cognitive Learning Process by Computer Graphics-Games: Towards More Efficient Learning Models
Author(s) -
Ahmet Orun,
Hüseyin Şeker,
John Rose,
Armaghan Moemeni,
Merih Fidan
Publication year - 2016
Publication title -
oalib
Language(s) - English
Resource type - Journals
eISSN - 2333-9721
pISSN - 2333-9705
DOI - 10.4236/oalib.1102329
Subject(s) - computer science , graphics , process (computing) , computer graphics , cognition , mathematics education , cognitive science , human–computer interaction , artificial intelligence , psychology , computer graphics (images) , programming language , neuroscience
Research group of Computer Sciences at DMU, Psychology Research Group at University of Birmingham and Reseach Group of Computer Science at University of Northumbria.With the latest developments in computer technologies and artificial intelligence (AI) techniques, more opportunities of cognitive data acquisition and stimulation via game-based systems have become available for computer scientists and psychologists. This may lead to more efficient cognitive learning model developments to be used in different fields of cognitive psychology than in the past. The increasing popularity of computer games among a broad range of age groups leads scientists and experts to seek game domain solutions to cognitive based learning abnormalities, especially for younger age groups and children. One of the major advantages of computer graphics and using game-based techniques over the traditional face-to-face therapies is that individuals, especially children immerse in the game’s virtual environment and consequently feel more open to share their cognitive behavioural characteristics naturally. The aim of this work is to investigate the effects of graphical agents on cognitive behaviours to generate more efficient cognitive models

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