KMi Seminars
MUP/PLE lecture series
This event took place on Friday 24 June 2011 at 14:00

 
Hendrik Drachsler Open University in the Netherlands

The growth of data in the knowledge society creates opportunities for new insights through advanced analysis methods based on information retrieval technologies. Educational institutions also create and own huge datasets on their students and course activities. But they make little use of the data when considering new educational services, recommending suitable peers or content, and improving the personalization of learning. Nevertheless, personalized learning is expected to have the potential to create more effective learning experiences, and accelerate the study time for students. In the educational world, only very limited datasets are publicly available and no agreed quality standards exist on the personalization of learning.
The dataTEL Theme Team aims to address these issues by advancing data driven research to gain verifiable and valid results and to develop a body of knowledge about the personalization of learning. In this context, new challenges emerge like unclear ethical, legal and privacy issues, suitable policies and formats to share data, required pre-processing procedures and rules to create sharable datasets, common evaluation criteria for personalization and recommender systems in TEL.
The lecture will give an overview about the latest developments in educational datasets research and give an outline how a dataset driven future in TEL could look like.

 
KMi Seminars Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Knowledge Management is...


Knowledge Management
Creating learning organisations hinges on managing knowledge at many levels. Knowledge can be provided by individuals or it can be created as a collective effort of a group working together towards a common goal, it can be situated as "war stories" or it can be generalised as guidelines, it can be described informally as comments in a natural language, pictures and technical drawings or it can be formalised as mathematical formulae and rules, it can be expressed explicitly or it can be tacit, embedded in the work product. The recipient of knowledge - the learner - can be an individual or a work group, professionals, university students, schoolchildren or informal communities of interest.
Our aim is to capture, analyse and organise knowledge, regardless of its origin and form and make it available to the learner when needed presented with the necessary context and in a form supporting the learning processes.