Abstract:

The field of learning sciences is represented by a growing community conceiving knowledge associated with educational system performance as well as assessment of technology-mediated learning processes. Accordingly, a recent evolutionary trend has been adopted by educationalists as well as learners due to rapid technological and social changes. Moreover, they are facing increasingly challenges arise in this time considering modifications of educational field applications.

During last decade of last century, educationalists have adopted recent Computer generation namely as natural intelligence as well as Information technology in order to reach optimality of learning processes' performance .In more details, it is worthy to refere to WHITE HOUSE REPORT(U.S.A.) in 1989; therein, it has been announced that decade (1990-2000) named as Decade of the brain. Furthermore, the overwhelming majority of neuroscientists have adopted the concept which suggests that huge number of neurons in addition to their synaptic interconnections constituting the central nervous system with its synaptic connectivity performing dominant roles for learning processes in mammals besides human. This motivation is specifically supported by what revealed by National Institutes of Health (NIH) in U.S.A. that children in elementary school, may be qualified to learn "basic building blocks" of cognition and that after about 11 years of age, children take these building blocks and use them.

This paper more specifically addresses the interdisciplinary research work originated from functional system for development of reading brain. Neurological researchers have recently revealed their findings about increasingly common and sophisticated role of the sixth computer generation of natural intelligence namely, Artificial neural networks (ANNs). That's applied for systematic realistic modeling of interdisciplinary discipline incorporating neuroscience, education, and cognitive sciences . Therefore, realistic ANN models have various structure to be in agreement with the nature of assigned brain functioning to be modeled. For example, as human learning takes place according to received stimuli, that is simulated realistically through self-organization paradigm by ANNs modeling. This piece of research adopts the conceptual approach of (ANN) models inspired by functioning of highly specialized biological neurons in reading brain based on the organization the brain's structures/substructures. Additionally, in accordance with the prevailing concept of individual intrinsic characterized properties of highly specialized neurons, presented models closely correspond to performance of these neurons for developing reading brain in a significant way. More specifically, introduced models concerned with their important role played in carrying out cognitive brain function' outcomes. The cognitive goal for reading brain is to translate that orthographic word-from into a spoken word (phonological word-form). In this context herein, the presented work illustrates via ANN simulation results : How ensembles of highly specialized neurons could be dynamically involved in performing the cognitive function of developing reading brain.

Keywords:

Artificial neural network modeling, Reading brain Performance, Associative memory, Self organized learning.