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This piece of research introduces an investigational systematic study of an interdisciplinary challenging phenomenon observed in natural world. Interestingly, this study belongs to the two emerging fields of nature-inspired computing (NIC) and computational intelligence (CI) with focusing on the physicsand biology-based approaches and algorithms .Herein, by more details this article concerned with the conceptual analysis and evaluation of quantified learning creativity phenomenon via simulation and modeling of two diverse natural biological systems (human & nonhuman creatures). More precisely, it is associated to diverse aspects of measurable behavioral learning performance of both biological systems. Therefore, this paper introduces comparative analogy between two diverse biological behavioral systems considering quantification of learning creativity. Referring to, the definition of Swarm intelligence which considered as a relatively new discipline that deals with the study of self-organizing processes both in nature and in artificial systems. Researchers in ethology and animal behavior have proposed many models to explain interesting aspects of social insect behavior such as self-organization and shapeformation. Accordingly, the presented study observed during human interactive tutoring/learning processes with natural environment. Versus ecological behavioral learning of swarm intelligence agents (Ants), while performing foraging process . Systematic investigational study of quantified human learning creativity phenomenon is an interdisciplinary, challenging, and interesting educational issue. At education field practice (classrooms) , while face to face tutoring sessions are performed, learning creativity phenomenon is detectable via bidirectional feedback between teacher and pupil. In short, this research work adopts comparative study of simulation and modeling for educational creativity issue considering two disciplinary approaches are namely: swarm intelligence, and neural networks. Both simulated realistically for systematic investigational modeling of creatures' creativity phenomenon observed in nature. Presented creativity models mainly consider observed behavioral learning of ant colony system in addition to in field educational classrooms. Conclusively, presented results herein, for both swarm intelligence and neural networks models seemed to be well promising for future more elaborate, systematic, and innovative research in evaluation of human learning creativity phenomenon regarding (NIC) and (CI). Keywords—Artificial Neural Networks Modeling, Ant Colony Optimization, Noisy Learning Enviornment, Optical Character Recognition, Swarm Intelligence. Hassan Mustafa Computer Engineering Department, Al-Baha Private College of Sciences Al-Baha, Kingdom of Saudi Arabia.On leave from Banha University (EGYPT) Fadhel Ben Tourkia, Computer Engineering Department, Al-Baha Private College of Sciences Al-Baha, Kingdom of Saudi Arabia

On Analytical Comparative Study Considering Quantified Learning Creativity Analogy versus Ant Colony Intelligence