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Title: Integration analysis of solutions based on software as a service to implement Educational Technological Ecosystems
Authors: García-Holgado, A.
Keywords: Technological Ecosystem
Software Ecosystem
Learning Ecosystem
Information Systems
Knowledge Management
Model Driven Development
Architectural Pattern
Human Factor
Issue Date: 7-Sep-2018
Publisher: Grupo GRIAL
Abstract: One of the main characteristics of the current Knowledge Society lies in the value of knowledge as an active resource in any kind of entity, from educational institutions to large corporate companies. Knowledge management emerges as a competitive advantage in such a way that entities allocate part of their resources to develop their capacity to share, create and apply new knowledges continuously over time. Technology, considered the engine, the core element, in the Information Society, becomes a support for learning, for the transformation of tacit knowledge into explicit, and also individual knowledge into group one. Internet, information and communication technologies and in particular the information systems go from being elements that guide the development of society to being tools whose development is guided by the needs of knowledge management and learning processes. The technological ecosystems, considered the evolution of the traditional information systems, are positioned as knowledge management systems that encompass both the technological component and the human factor. In the case that knowledge management is aimed at fundamentally supporting learning processes, the technological ecosystem might be called learning ecosystem. The metaphor of ecosystems, which comes from the biology area, is used in different contexts to convey the evolutionary nature of processes, activities and relationships. The use of the natural ecosystem concept is applied to the technological field to reflect a set of characteristics or properties of natural ecosystems that can be transferred to technological ecosystems or software ecosystems in order to provide solutions that allow solving knowledge management problems, and which adapt to the constant changes suffered by any kind of entity or context in which some type of technological solution is deployed. Despite the advantages offered by technological ecosystems, the development of this type of solutions has greater complexity than traditional information systems. The problems inherent to software engineering, such as the interoperability between components or the evolution of the ecosystem, are combined with the difficulty of managing complex knowledge and the diversity of people involved. The different challenges and problems of technological ecosystems, primarily those focused on managing knowledge and learning, require improving the definition and development processes of this type of technological solutions. The present PhD thesis focuses on providing an architectural framework that allows improving the definition, development and sustainability of technological ecosystems for learning. This framework will be composed, mainly, of two results associated with this research; an architectural pattern that allows to solve the problems detected in real learning ecosystems and a learning ecosystem metamodel, based on the pattern, that allows to apply Model Driven Engineering to sustain the definition and development of learning ecosystems. To carry out the research, three cycles have been defined following the Action-Research methodological framework. The first cycle was focused on the analysis of several real case studies in order to obtain a domain model of the problem. Technological ecosystems for knowledge and learning management deployed in heterogeneous contexts have been analyzed, in particular, the University of Salamanca, the GRIAL research group and the European project TRAILER (focused on managing informal learning at institutions and companies). As a result of this cycle, a set of characteristics that a technological ecosystem must consider was detected and an architectural pattern was defined. The pattern allows laying the foundations of the ecosystem, giving solution to some of the detected problems and ensuring the flexibility and adaptability of the components of the ecosystem in order to allow its evolution. The second cycle was focused on the improvement and validation of the architectural pattern. The problems detected in the previous cycle was modeled using Business Process Model and Notation. To do this, the problems related to similar knowledge management processes was clustered and a diagram with a high abstraction level was made for each cluster of problems. Then, for each diagram, once again the problems to be solved was identified and a new diagram was defined applying the pattern. This allowed to validate the architectural pattern and lay the foundations for its formalization. Finally, the third cycle raised the Model Driven Development of technological ecosystems for the knowledge and learning management. In particular, a learning ecosystem metamodel, based on the architectural pattern specified in the previous cycle, was defined. The metamodel was validated through a set of model-to-model transformations automated through transformation rules. In order to carry out this process, a platform specific metamodel was defined. This metamodel provides a set of recommendations, both technological and human, to implement learning ecosystems based on open source software. The learning ecosystem metamodel and the platform specific metamodel to define ecosystems based on open source software provide the necessary guides to model learning ecosystems that solve the main problems detected in this type of software solutions. The three real case studies that were developed to validate the results obtained during the Action-Research cycles, especially the architectural pattern to define learning ecosystems, the learning ecosystem metamodel and the platform specific metamodel to model ecosystems based on open source software, allow us to conclude that it is possible to improve the definition and development of technological ecosystems focused on knowledge and learning processes management. More specifically, the use of model-driven engineering, based on a solid architectural proposal, allows defining learning ecosystems that evolve and adapt to the changing needs of the environment and users, as well as solving a set of common problems identified in this type of technological solutions.
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