DSpace Comunidad : Emerging interactive systems for education session at the HCI International 2017 Conference, held in Vancouver, Canada, 9 - 14 July 2017
http://repositorio.grial.eu/handle/grial/932
Emerging interactive systems for education session at the HCI International 2017 Conference, held in Vancouver, Canada, 9 - 14 July 20172024-03-28T17:55:32ZAdaptive and cooperative model of knowledge management in MOOCs
http://repositorio.grial.eu/handle/grial/958
Título : Adaptive and cooperative model of knowledge management in MOOCs
Autor : Sein-Echaluce, M. L.; Fidalgo-Blanco, Á.; García-Peñalvo, F. J.
Resumen : One of the characteristics of Massive Open Online Courses (MOOC) is the heterogeneity of their participants’ profiles and, for the most traditional MOOC model, this is an important cause of the low completion rate. The MOOC model presents two apparent antagonistic concepts, globalization and diversity. MOOCs represent globalization (participants have to be adapted to the course) and their participants represent diversity. The authors of this paper argue that both concepts complement each other; that is, a MOOC can adapt the contents and navigation to the diversity of participants; and in turn the participants themselves can increase and improve the contents of the MOOC, through heterogeneous cooperation, to encourage massive learning. To proof it, this paper presents a new model, called ahMOOC, combining the hybrid-MOOC (hMOOC) and the adaptive MOOC (aMOOC). The hMOOC allows integrating characteristics of xMOOCs (based on formal e-training) with cMOOCs (based on informal and cooperative e-training). The aMOOC offers different learning strategies adapted to different learning objectives, profiles, learning styles, etc. of participants. The ahMOOCs continues having a lower dropout rate (such as hMOOC) than the traditional MOOCs. The qualitative analysis show the capacity of participants, with heterogeneous profiles, to create, in a cooperative and massive way, useful knowledge to improve the course and, later, to apply it in their specific work context. The study also shows that participants have a good perception on the capabilities of the ahMOOC to adapt the learning process to their profiles and preferences.2017-07-13T00:00:00ZPresentation of the paper “Adaptive and cooperative model of knowledge management in MOOCs” in HCII 2017
http://repositorio.grial.eu/handle/grial/957
Título : Presentation of the paper “Adaptive and cooperative model of knowledge management in MOOCs” in HCII 2017
Autor : Sein-Echaluce, M. L.; Fidalgo-Blanco, Á.; García-Peñalvo, F. J.
Resumen : This is the presentation of the paper entitled “Adaptive and cooperative model of knowledge management in MOOCs” in the Emerging interactive systems for education session at the HCI International 2017 Conference, held in Vancouver, Canada, 9 - 14 July 2017.
One of the characteristics of Massive Open Online Courses (MOOC) is the heterogeneity of their participants’ profiles and, for the most traditional MOOC model, this is an important cause of the low completion rate. The MOOC model presents two apparent antagonistic concepts, globalization and diversity. MOOCs represent globalization (participants have to be adapted to the course) and their participants represent diversity. The authors of this paper argue that both concepts complement each other; that is, a MOOC can adapt the contents and navigation to the diversity of participants; and in turn the participants themselves can increase and improve the contents of the MOOC, through heterogeneous cooperation, to encourage massive learning. To proof it, this paper presents a new model, called ahMOOC, combining the hybrid-MOOC (hMOOC) and the adaptive MOOC (aMOOC). The hMOOC allows integrating characteristics of xMOOCs (based on formal e-training) with cMOOCs (based on informal and cooperative e-training). The aMOOC offers different learning strategies adapted to different learning objectives, profiles, learning styles, etc. of participants. The ahMOOCs continues having a lower dropout rate (such as hMOOC) than the traditional MOOCs. The qualitative analysis show the capacity of participants, with heterogeneous profiles, to create, in a cooperative and massive way, useful knowledge to improve the course and, later, to apply it in their specific work context. The study also shows that participants have a good perception on the capabilities of the ahMOOC to adapt the learning process to their profiles and preferences.2017-07-20T00:00:00ZA metamodel proposal for developing learning ecosystems
http://repositorio.grial.eu/handle/grial/956
Título : A metamodel proposal for developing learning ecosystems
Autor : García-Holgado, A.; García-Peñalvo, F. J.
Resumen : The definition and development of learning ecosystems is a complex process with a wide range of requirements. Although two different institutions or companies share the same problems and goals regarding their learning and training processes, the learning ecosystems to support them are different. The components of the ecosystem, including the human factor as a key element, and the relationships between them, change over time. In other words, learning ecosystems evolve as natural ecosystems; there are many factors, both internal and external, that influence an entity. The authors have defined and developed different learning ecosystems. Moreover, they have transferred the same learning ecosystem, specifically a learning ecosystem for knowledge management in a PhD Program, to different domains. These experiences have provided the required information to define the ecosystems metamodel following the Model Driven Architecture proposed by the Object Management Group. The aim of this metamodel is define a Domain Specification Language to develop learning ecosystems.2017-07-13T00:00:00ZCan we apply learning analytics tools in Challenge Based Learning contexts?
http://repositorio.grial.eu/handle/grial/955
Título : Can we apply learning analytics tools in Challenge Based Learning contexts?
Autor : Conde-González, M. Á.; García-Peñalvo, Francisco J.; Fidalgo-Blanco, Á.; Sein-Echaluce, M. L.
Resumen : The information and Communication Technologies changes how we interact with others and with the information. It can be really accessed at anytime and anywhere. Future professionals should be ready for this reality which requires changes in traditional teaching and learning methods. Challenge Based Learning is an example of them. This method poses challenges to students that they should solve employing the technology they use during their daily life. The evaluation of challenges solutions should take into account students’ final outcomes but also the interactions that take place between them. This could be very hard given the wide choice of tools that students can apply. Learning analytics tools could be a solution. This paper reviews and classifies the tools applied in several Challenge Based Learning experiments and describes different possibilities to apply Learning Analytics. From this research, it is possible to conclude that Learning Analytics can be applied in Challenge Based Learning contexts, but it is desirable to use a single platform to group the tools employed to solve the challenge.2017-07-13T00:00:00Z