Dynamic Distributed Balancing of Local, Group and Organizational Harmonies: Case of Multitrack Multistage eLearning Design

AUTHOR
Alexander Vengerov

ABSTRACT

This paper is the part of the project exploring a new model of learning organization called MultiTrack MultiStage (MTMS) pattern. The paper analyzes and generalizes the lessons of the 5 year experience with MTMS eLearning design to specific methods and mechanisms of the art of dynamic balancing of local, group, and global harmonies in dynamic distributed technology-intensive socio-pragmatic systems.

The growing problems of complexity, uncertainty, and instability (CUI) in complex adaptive systems tend to further increase with the ubiquity and proliferation of information and communication technologies (ICT), dramatically increasing mutual sensitivity of systems components. The CUI problems make many existing methods of analysis and design of socio-pragmatic systems obsolete. The new approaches have yet to be developed. They are being tackled in various domains of human research. The paper analyzes approaches from such areas as situated cognition, ethics, and philosophy; utility computing and computational grids; grounded research, complex adaptive systems, and holistic engineering while drawing from the experience gained from the specific case of eLearning design dealing with the above mentioned type of environments and situations.

Already Aristotle in his Nicomachean Ethics saw the main problem in balancing of various forces to some harmonious Golden Mean state. This concept has been significantly enhanced with the development of The Dynamical Systems Theory and other disciplines dealing with the phenomena of complexity and emergence as the view of patterns evolving from some form of balncing contextual forces. Action theory concerns with generalization of agent’s behaviour as a fit to the particular a situation. The tight interconnetion of individual desires, beliefs, and perceptions in the search of the best actions, plans, and strategies fullfilling the desires under the given circumstances formed the foundation of many architectures of artificial intelligent agents as the view on the dynamic interaction of this forces. In economics and other social sciences within the framework of Rational Choice this view underlies much of existing approaches to norms, ethics, justice, etc. However, it has been found that the increasing CUI properties of many situations might upset reasoning based on causality and result into some dynamic evolutionary processes with undetermined causes and uncontrollable and unpredictable ends.

The paper analyzes the emerging situated approaches in ethics, economics, philosphy and sciences focusing on ongoing processes and situational dynamics that determine (or influence) the tactical actions and evolving patterns of behavior. The problem with CUI situations is in the difficulties of applying symbolic reasoning and thus exercize control over the situational evolution. Connectionst approach to the growing power of contexts over evolving patterns has been used in complex systems analysis resulting in studies, modeling, and application of non-symbolic processes supporting overall systems adaptivity and viability. Methods of soft computing including various forms of fuzzy, evolutionary, and reinforcement learning of current contexts use these processes for determining the best course of actions under the curcumstances of the given situations. The growing holistic properties of the situations agents are in can impede not only the controlling abilities over the one’s future, but make it difficult even to properly formulate it.

In most complex modern environments found in computational grids, we can see multiple interwoven inetersts, conflicts, and perceptions of local situations and views of the proper “global order.” There is a growing shift in this area from behaviors aiming not at particular (often changing and fuzzy) goals but at more general utilities, leaving situation- action-goal dynamics to the holistic evolutionry forces. Acknowledging the importance of the situational distributed multiagent learning in the process of balancing the perception of local, group, and higher forms of harmony, the present paper offers the analysis and some generalizations of the experience with one of the most complex patterns of learning design (MTMS) as a socio-pragmatic technology-based complex system. It is based on the methods of management of the learning ecology, gently steering (since control is impossible and even unethical under the circumstance) its dynamics to the advantageous forms and its results meeting learning objectives.

The MTMS pattern deals with scalable eLearning environments capable to include hundreds of participants as well as automated and semi-automated resources and processes. This view reflects the problem, which the MTMS pattern was designed to solve – the one of an effective, efficient, and self-correcting learning process for students with diverse individual educational goals, prior knowledge, skills, and socio-cultural backgrounds. Such diversity results in methods and mechanisms of steering this micro-society toward planned educational goals. These mechanisms and methods are very different from those in more homogenous classes. The specifics of MTMS is in the fact that the tight control of learning activities in the described situation is not only impossible but also unethical, leading to the need of stimulating the individual design of learning contexts with desirable degree of exploration, experiences, and social interactions enriched and corrected by the very diversity of actors. After the analysis of MTMS performance the paper offers some generalization of the methods and patterns of balancing local, group, and global harmonies that include the mix of the social and pragmatic utilities and experiences.

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