Generally, Analysis of learning creativity phenomenon is an interesting and challenging issue associated with educational practice. Moreover, that phenomenon is tightly related to main human brain functions (Learning and Memory). So, creative individuals are characterized by their distinct capabilities in performing both brain functions. Additionally, educationalists as well as psychologists, for a long time ago and until recently, have been interesting in searching for quantitative investigation of that challenging issue. In the field of education, practical evaluation of learners' performance, - during tutoring session(s) - may result in observation of creativity phenomenon. Herein, this work introduces an interdisciplinary novel approach concerned with analysis of quantifying learning creativity phenomenon. That is fulfilled by adopting Artificial Neural Networks modeling for realistic simulation of synaptic connectivity dynamics (equivalently, synaptic plasticity). By some details, presented work considered two main design parameters of Artificial Neural Networks. Namely they are, gain factor (of neuronal sigmoid activation function), and learning rate value. Both parameters Synaptic Plasticity inside the brain. Obviously, individuals characterized by various values of gain factor value as well as learning rate parameter are well relevant to quantify there learning creativity. Conclusively, obtained results motivate future research for systematical investigational study in depth considering the effect of congenital and/or hereditary factors on learning creativity phenomenon
Generally, Analysis of learning creativity phenomenon is an interesting and challenging issue associated with educational practice. Moreover, that phenomenon is tightly related to main human brain functions (Learning and Memory). So, creative individuals are characterized by their distinct capab...
مادة فرعية
International Arab Journal of e-Technology