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
 

Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.