Computations related to learning processes within an organizational social network area require some network model preparation and specific algorithms in order to implement human behaviors in simulated environments. The proposals in this research model of collaborative learning in an organizational social network are based on knowledge resource distribution through the establishment of a knowledge flow. The nodes, which represent knowledge workers, contain information about workers' social and cognitive abilities. Moreover, the workers are described by their set of competences, their skill level, and the collaborative learning behavior that can be detected through knowledge flow analysis. The proposed approach assumes that an increase in workers' competence is a result of collaborative learning. In other words, collaborative learning can be analyzed as a process of knowledge flow that is being broadcast in a network. In order to create a more effective organizational social network for co-learning, the authors found the best strategies for knowledge facilitator, knowledge collector, and expert roles allocation. Special attention is paid to the process of knowledge flow in the community of practice. Acceleration within the community of practice happens when knowledge flows more effectively between community members. The presented procedure makes it possible to add new ties to the community of practice in order to influence community members' competences. Both the proposed allocation and acceleration approaches were confirmed through simulations.Keywords: organizational social network, computational models, collaborative learning behavior, knowledge flow, community of practice . to maximize worker knowledge level (over a planning horizon) through sharing in different organizational environments was presented by Dong et al. (2012). In this approach, organizations that support multiple skills and have workers with varying levels of knowledge in these skills were examined. The algorithm developed identified the best set of knowledge transfers in each period in order to maximize the total weighted knowledge level of a given organization over a planning horizon. As a result, the mixed integer programming model and its related heuristics were formulated to facilitate the systematic analysis and understanding of effective knowledge flows. Neither of these approaches included a community-of-practice component or roles in the knowledge flow.Depending on the analysis concept, there are different approaches to collaboration network analysis (Różewski, 2010). The queuing theory can be used to efficiently optimize a telecommunications network (Różewski and Ciszczyk, 2009). In such a situation, the node represents various computer stations that are able to signal regeneration or data distribution.Another approach to collaboration network analysis is from the workflow point of view (Wang et al., 2006). In this context the network's unit is a task and we are looking for workload optimization. Moreover, the nodes correspond to work...

No abstract

No abstract

El método R5 como estrategia pedagógica para mejorar las competencias tecnológicas de los docentes de primaria en la enseñanza de la habilidad comunicativa en inglés. Autor(es).

Abstract. The competence-based learning-teaching process is a significant approach to the didactical process organization. In this paper the mathematical model of the competence-based learning-teaching process is proposed. The model integrates three models: a knowledge representation model (based on the ontological approach), a motivation model (as a behavioral-incentive model) and a servicing model (in a form of the queuing model). The proposed integrated model allows to control the learning-teaching process on different levels of management. The learning-teaching process can be interpreted as competence-based due to Open and Distance Learning (ODL) philosophy. We assume that the competence is a result of fundamental, procedural and project knowledge acquisition in accordance to the incoming European Qualification Framework.