On Simulation of Brain Based Learning Paradigms ( Neural Networks Approach )

Introduction The field of the learning sciences is represented by a growing community internationally. Many experts now recognize that conventional ways of conceiving knowledge, educational systems and technology-mediated learning are facing increasing challenging issues in this time of rapid technological and social changes. Since beginning of last decade, Artificial Neural Networks (ANN S ) models have been adopted to investigate systematically mysteries of human brain, the most complex biological neural system, [1]. Furthermore, due to recently excessive progress in information technologies and computer applied at the field of the learning sciences, some complex interdisciplinary educational issues arise in practice. That’s motivated by evaluation trend in learning science incorporated Nero-physiology, psychology, and cognitive science, [2][3][4]. More specifically, this paper addresses an investigational and systemic approach associated with interdisciplinary research work originated from mental stimulation and brain-based learning [5][6]. Furthermore, other research fields such as neurology, social science, psycho-immunology; behavioral genetics, psychobiology, cognitive science, neuroscience and physiology play a role in evaluation and analysis of challenging educational issues [5]. Recently, neurological researchers have revealed that in order to promote and encourage maximum learning capacity within learners' brains. It is vital to enhance learning performance of arbitrary educational process via mental stimulation of brains' synapses and neurons. Those are mainly responsible for perception of carried valuable knowledge. Therefore, as tutors adopt brain based learning style, it is needed to be able to stimulate, encourage and hook our learners into increasing of their learning performance capacity about many different subjects and topics [6][7]. In the neural networks context, the perception function in learners' brain is well performed during mental stimulation by interactive engagement of tutors with learners. This piece of research presents specifically an overview on an interdisciplinary research issue integrating educational field phenomena with the modeling of brain based learning using Artificial Neural Networks (ANN). In more details, the adopted ANN model simulates realistically the brain based learning style by a supervised with a teacher paradigm. That paradigm proceeds via bidirectional communication between a tutor and his learner(s). Accordingly, it realistically represents interactive engagement learning strategy which observed at our classrooms as (face to face tutoring). In practical educational environment, brain is intimately involved in and connected with, everything instructors and learners do while face to face tutoring sessions. It is an essential premise: face to face tutoring represents about one fourth of total learning achievement at the open learning system's environment [8]. Moreover, it considered as an engagement (interactive) strategy of brain based learning in order to enhance learners' capacity. In other words, in the educational phenomenon context, brain based learning style may be strategically performed by either by interaction engagement with a teacher (face to face tutoring) or with computer aided learning software. Moreover, our obtained results shown to be supported by two recently published research papers. Finally, obtained result supports improvement of learning creativity following increase of synaptic connectivity in addition to the neurobiological research work concerned with the other half of the brain (Glial cells) [9].