TITLE:
A Quantisation of Cognitive Learning Process by Computer Graphics-Games: Towards More Efficient Learning Models
AUTHORS:
Ahmet Bahadir Orun, Huseyin Seker, John Rose, Armaghan Moemeni, Merih Fidan
KEYWORDS:
Computer Graphics, Cognitive Learning, Bayesian-Networks
JOURNAL NAME:
Open Access Library Journal,
Vol.3 No.1,
January
28,
2016
ABSTRACT: 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.