Modeling of Next Generation Digital Learning Environments : Complex Systems Theory.

Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Foreword -- Introduction -- 1. A Virtual Learning Environment seen as a System of Instrumented Activities -- 1.1. From school radios to MOOCs: a retrospective glance at the evolution of instrumented activities in education -- 1.1.1. Educational technologies, ICT, ICTs for teaching, common ICTs? -- 1.1.2. A broad variety of technologies in education -- 1.1.3. Learning to put knowledge, expertise and interpersonal skills into practice -- 1.1.4. Learning modes -- 1.1.5. Learning modes in education -- 1.1.6. ICT, learning and pedagogical theories: an interrelated revolution -- 1.1.7. From objectivist epistemology to school radio and television -- 1.1.8. From behaviorism to computer-assisted learning -- 1.1.9. From construstivism to microworlds -- 1.1.10. From social constructivism to CLE, CSCL and cMOOC -- 1.1.11. Learning in an open network: from connectivism to MOOCs -- 1.1.12. Synthesis of these evolutions -- 1.2. VLEs: a system of instrumented activity -- 1.2.1. Virtual learning environments (VLEs) -- 1.2.2. The principles of the systemic paradigm -- 1.2.3. The steps involved in the systemic approach -- 1.2.4. VLEs seen as open systems -- 1.2.5. VLEs seen as systems of instrumented activity -- 1.3. Conclusion -- 2. Modeling Instrumented Activity at the Heart of the Virtual Environment -- 2.1. Introduction -- 2.2. Modeling instrumented activity, yes, but why? -- 2.2.1. What type of model are we talking about? -- 2.2.2. Models for multiple uses -- 2.2.3. Models with specific uses -- 2.3. Contour, components and hierarchical levels of a system of instrumented activity -- 2.3.1. Perimeters, objects and components -- 2.3.2. Three levels (macro, meso, micro) associated with business processes -- 2.3.3. An example of distance learning device analysis.

2.3.4. Associated levels, objects and models -- 2.4. Summary of models and modeling languages -- 2.4.1. Models of pedagogical engineering (EML) -- 2.4.2. Training engineering models -- 2.4.3. Adaptive models -- 2.4.4. Systemic models of activity -- 2.4.5. Systemic models of complexity -- 3. Models of Instrumented Activity Challenged by Technopedagogical Innovations -- 3.1. Introduction -- 3.2. The Vygotskien model and its expansion -- 3.2.1. Digital ink: towards a new virtual learning environment design -- 3.2.2. Use of tablets (iPads) in school contexts -- 3.3. Expansion of Engeström's model -- 3.3.1. Looking for a unifying model in long-distance learning -- 3.3.2. First expansion of Engeström's model for designing a CLE -- 3.4. New context of usage and new expansion -- 3.4.1. Digital workspaces in schools: online text books -- 3.4.2. Second expansion of the model: facilitating the analysis of online textbooks -- 3.5. Expansion of pedagogical and training engineering models -- 3.5.1. Resistance to pedagogical engineering models -- 3.5.2. Evolution towards training engineering models -- 3.6. MOOC models to build -- 3.7. Conclusion on the resistance conditions of virtual learning environment models -- 4. The Digital Learning Environment in the Paradigm of Systemic Complexity Modeling -- 4.1. Complex systems theory and theoretical framework -- 4.1.1. Definition of a complex system -- 4.1.2. Modeling of complex systems -- 4.2. Argument in favor of the application of the complex systems theory to the modeling of latest-generation DLEs -- 4.2.1. Introduction -- 4.2.2. DLE: a complex system -- 4.2.3. Complexity theory: at the heart of the connectivist learning design -- 4.2.4. Conceptual analogy between the SM of complexity and SM of activity -- 4.2.5. Modeling these environments with suitable languages -- 4.2.6. Enrolling in a forward-looking approach.

5. Modeling a DLE Perceived as a Complex System -- 5.1. Finalized and recursive processes in an active environment -- 5.1.1. Identifiable finalized processes (functions) -- 5.1.2. Recursive processes -- 5.1.3. Representation of the processes and functional levels of the system -- 5.1.4. The eight constituent functions of a DLE applied to systemic modeling -- 5.2. Synchronic processes (the system performs) -- 5.2.1. Identifying the active presence of interrelationships -- 5.2.2. Establishing an input and output value inventory for each process -- 5.2.3. Representing data flow and functional dependencies between processes -- 5.3. Diachronic processes (the system becomes) -- 5.3.1. Typical sequences (or scenarios) and even tracking -- 5.3.2. Traces left by events -- 5.3.3. The states and state diagrams -- 5.3.4. Process descriptions -- 5.4. A system capable of processing information and deciding its own behavior -- 5.5. A model based on analysis data -- 5.5.1. A model constructed from analysis data -- 5.5.2. Provenance and data collection -- 5.5.3. Data analysis -- 6. Modeling and Simulation of an MOOC: Practical Point -- 6.1. Modeling an MOOC -- 6.1.1. Package and use case diagrams -- 6.1.2. "Class" diagrams -- 6.1.3. State transition diagrams -- 6.1.4. Sequence diagrams -- 6.2. MOOC simulation -- 6.2.1. The program structure -- 6.2.2. The script -- 6.2.3. Related files -- 6.2.4. Parameters that come into play and initialization values -- 6.2.5. Progress in the chapters -- 6.3. Simulation result -- 6.3.1. Level of total understanding -- 6.3.2. Level of understanding of the module -- 6.3.3. Level of understanding of the chapter -- 6.4. Putting the obtained results into perspective -- Conclusion -- Appendices -- Appendix 1. Functional model notation -- Appendix 2. Dynamic model notation -- Appendix 3. MOOC.py and Quiz.py -- Appendix 4. Étudiants.py.

Appendix 5. Chapitre.py -- References -- Index -- Other titles from iSTE in Science, Society and New Technologies -- EULA.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.