MUP/PLE lecture series
This event took place on Thursday 23 June 2011 at 14:00
Hendrik Drachsler Open University in the Netherlands
Technology-enhanced learning aims to design, develop and test socio-technical innovations that will support and enhance learning practices and knowledge sharing of individuals and organizations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. With the increasing use of Learning Management Systems, Personal Learning Environments, and Data Mashups the TEL field, became a promising application area for information retrieval technologies and Recommender Systems to suggest most suitable learning content or peers to learners. The renewed interest in information retrieval technologies in TEL reveals itself through an increasing number of scientific events and publications combined under the research term Learning Analytics. Learning Analytics has the potential for new insights into learning processes by making so far invisible patterns in the educational data visible to researchers and develop new services for educational practice.
This lecture attempts to provide an introduction to Recommender Systems for TEL, as well as to highlight their particularities compared to recommender systems for other application domains. Finally, it will outline the latest developments of Recommender Systems in the area of Learning Analytics.
This event took place on Thursday 23 June 2011 at 14:00
Technology-enhanced learning aims to design, develop and test socio-technical innovations that will support and enhance learning practices and knowledge sharing of individuals and organizations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. With the increasing use of Learning Management Systems, Personal Learning Environments, and Data Mashups the TEL field, became a promising application area for information retrieval technologies and Recommender Systems to suggest most suitable learning content or peers to learners. The renewed interest in information retrieval technologies in TEL reveals itself through an increasing number of scientific events and publications combined under the research term Learning Analytics. Learning Analytics has the potential for new insights into learning processes by making so far invisible patterns in the educational data visible to researchers and develop new services for educational practice.
This lecture attempts to provide an introduction to Recommender Systems for TEL, as well as to highlight their particularities compared to recommender systems for other application domains. Finally, it will outline the latest developments of Recommender Systems in the area of Learning Analytics.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
New Media Systems is...
Our New Media Systems research theme aims to show how new media devices, standards, architectures and concepts can change the nature of learning.
Our work involves the development of short life-cycle working prototypes of innovative technologies or concepts that we believe will influence the future of open learning within a 3-5 year timescale. Each new media concept is built into a working prototype of how the innovation may change a target community. The working prototypes are all available (in some form) from this website.
Our prototypes themselves are not designed solely for traditional Open Learning, but include a remit to show how that innovation can and will change learning at all levels and in all forms; in education, at work and play.
Check out these Hot New Media Systems Projects:
List all New Media Systems Projects
Check out these Hot New Media Systems Technologies:
List all New Media Systems Technologies
List all New Media Systems Projects
Check out these Hot New Media Systems Technologies:
List all New Media Systems Technologies



