Educational modeling

Delivering flexible services for IMS Learning Design using widgets: achievements, limitations and prospects

Date

2011-01-14

Lecturer

Dai Griffiths (CETIS, UK)

Summary

The IMS LD specification has attracted considerable interest since its publication in 2003 as a means of modelling and orchestrating educational activities. It aims to make these models interoperable, but one major barrier to this, has been the inability to make a range of services available across multiple systems. This has also meant that Learning Design runtime systems are often rather impoverished with regard to services.

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IMS Learning Design services integration: use experiences

Date

2011-01-14

Lecturer

Luis de la Fuente Valentín (UC3M)

Summary

The actual web offers a wide catalogue of tools (the so called web 2.0 applications) that are related to many different topics. Most of those tools can be used in educational practices to facilitate activities. IMS Learning Design (IMS LD) is a specification that allows reusing activity sequences of arbitrary complexity. Therefore, a sequence (called UoL) that has shown to be successful can be used several times at a low implementation cost. When introducing web 2.0 tools as part of one of these sequences we find that the resulting UoL loses the most relevant IMS LD characteristics: interoperability, reusing capacity, adaptability and collaboration capacity.

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Authoring and reengineering of Learning Designs: the approach

Date

2011-01-14

Lecturer

Iván Martínez (UCM)

Summary

The Educational Modeling Languages (EMLs) allows instructors to describe and formalize the learning processes by a document called learning design. These learning designs deal both with the educational contents and also with the complementary activities needed to achieve an effective use of the educational contents and foster the learning process. The learning designs formalized with an EML have the advantage that can be automatically processed by a software tool. This automatic processing of a learning design allows for the automation of the virtual learning environment configuration to support the teaching process and for the execution of the activities represented in the learning design. This explicit representation of the teaching process has additional advantages, such as these learning designs can be reused by other instructors just as an example of good practices or as an starting point to create their particular learning design specifically adapted for their learners’ needs.

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CopperCore integration with Open Wonderland for the execution of learning units in virtual worlds

Date

2010-12-10

Lecturer

David Maroto (UC3M)

Summary

Immersive spaces, and in particular the three-dimensional virtual worlds, are increasingly used in the learning process of students, mainly for skills development and collaborative learning. These virtual worlds make the learning process more attractive, mainly due to its rich graphical interface and sense of "game" that they give to the educational process.

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Three-dimensional worlds: the integration of IMS LD in virtual worlds

Date

2010-12-10

Lecturer

Juan Carlos Vidal Aguiar (USC)

Summary

3D Educational environments are virtual worlds designed to encourage interaction and communication between participants of a course, drawing on immersion in virtual worlds of students and teachers. In recent years we have developed a number of 3D learning environments which aim to simulate real-world environments (Campus, classrooms, etc..) in which teaching activities take place. In these environments, however, did not avail the benefits of virtual education in terms of management and adaptation of learning activities to the students and teachers’ behavior and evolution.

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Learning from experience: algorithms for learning patterns and possible applications in e-learning environments

Date

15/10/2010

Lecturer

Alicia Rodríguez Carrión (Universidad Carlos III de Madrid)

Summary

Usually we tend to focus on the learning process of students, but educators can learn by observing the behavior of students and adapt the learning process according to their comments? There are certain algorithms that can learn patterns that repeat users. Our current research focuses on using these algorithms in mobile environments, learning the routes that often follow a user to predict where it's going to go in the future. The talk will show the basic operating principles of these algorithms and some examples of how they might apply to e-learning environments.

 

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