Abstract
Investigational analysis and evaluation of cooperative learning phenomenon is an interdisciplinary and challenging educational research issue. Educationalists have been interesting in modeling of human's cooperative learning to investigate its analogy with some learning aspects of observed social insect behavior. Specifically, this paper presents realistic modeling inspired from interdisciplinary integrated fields of ecology, education ,and animal behavior learning sciences. Presented modeling considers cooperative behavioral learning at ant colony system (ACS). That's motivated by qualitative simulation results obtained after running of an ACS algorithm searching for optimal solution of Travelling Salesman Problem (TSP). In the context of computational intelligence ; cooperative ACS algorithm reaches optimal TSP solution analogously to convergence process of Hebbian coincidence learning paradigm. Moreover, suggested mathematical modeling presents diversity of positive interdependence aspect observed during human's interactive cooperative learning. Interestingly, presented analysis and evaluation of mathematically modeled practical insights of adopted phenomenon, may shed light on promising future enhancement of cooperative learning performance.
Highlights
In face to face tutoring, the phase of interactive cooperative learning is an essential paradigm aiming to improve any Open Learning System (OLS) performance
It has been declared that cooperative learning among studying agents,contributes about one fourth of attained output learning achievement during face to face tutoring sessions at OLS [1]
Versus human's cooperative learning performance observed among students at OLS during face to face tutoring sessions
Summary
In face to face tutoring , the phase of interactive cooperative learning is an essential paradigm aiming to improve any Open Learning System (OLS) performance. Considering observed resemblance between human's interactive cooperative learning at OLS, and cooperative behavioral learning function (among ants) at Ant Colony System(ACS) Mathematical modeling for both disciplined learning paradigms has been presented commonly. In computational intelligence context; resemblance between two neuronal and non-neuronal disciplines observed in nature have been comparatively presented They are respectively; cooperative behavioral learning among number of place field neuronal cells (at hippocampus rat's brain area) contributing in solving reconstruction problem inside 8-Figure maze[3]. Considering comparative context, analogy between two types of distinct cooperative learning performance associated with computational intelligence agents (ants & neurons) has been verified by obtained interesting results. Presented comparative mathematical modeling as well as results obtained after programs' running, may be promising in optimal improvement of educational achievement(s) at face to face tutoring sessions during Open Learning Processes. By the end of this work, an Appendix is attached which illustrates a simplified macro level flowchart which describes algorithmic steps of simulation program for Hebbian learning using Artificial Neural Network ANN
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