Studentship Vacancies

Semantic Adaptivity and Social Networking in Personal Learning Environments

The aim of this PhD project is to employ a combination of Semantic and Social Web technologies in order to enhance adaptivity and networking in Personal Learning Environments (PLEs). The PhD student will explore new ways of making the learning process adaptive to the learner’s needs through the use of ontologies and metadata, as well as enabling the learner to actively engage with a community sharing common learning objectives.

Background

Technology-Enhanced Learning (TEL) has shown considerable growth over the past years. However, most TEL environments are still facing limitations in terms of personalisation and adaptation to the learner's needs and preferences. In many cases, TEL environments offer a rigid, course-based learning experience, which does not address the particular interests and needs each individual learner has.

The realisation of this shortcoming has led to the emergence of Personal Learning Environments (PLEs), featuring sets of lightweight services and tools that are controlled by individual learners. Nevertheless, PLEs have limited capabilities in terms of adapting the learning processes of individual learners, or supporting collaborative learning within networked communities of learners.

Objectives

Emerging technologies from the Semantic and the Social Web can potentially play a key role in addressing these limitations. The Social Web offers simple but engaging and widely adopted services like social networking, blogging, collaborative authoring, and more. One objective of this project is to employ these technologies in order to engage learners into collaborative learning and formulating active communities of peer-assisted learners.

On the other hand, the Semantic Web offers metadata and machine processability to learning resources and services. This project aims in creating a semantic knowledge base for PLEs, by using metadata and ontologies to annotate learning resources, model learner profiles, and accordingly adapt the learning process to suit each profile. In addition, modelling the underlying semantics of learner profiles will help match profiles with more accuracy, thus improving automated recommendations and networking between learners with similar backgrounds and learning goals.

Bibliography

Kravcik, M. et al. (2008). Current and Future Perspectives for Personalized Adaptive Learning. PROLEARN Deliverable D1.13, available at http://www.prolearn-project.org/articles/wp1/index.html

The bursary will cover the student fees and living expenses of around 1050 pound Sterling/month.

For further information on this PhD project please contact:

Dr Alexander Mikroyannidis
Research Fellow

+44 (0)1908 652073

Dr Peter Scott
KMi Director

Tel. +44 (0)1908 655763.

Additional Information:

The Knowledge Media Institute (http://kmi.open.ac.uk) is home to internationally recognised researchers in semantic web, artificial intelligence, cognitive science, human-computer interaction, information retrieval and multimedia processing. KMi offers students an intellectually challenging environment with exceptional research and computer facilities. You will be joining a dynamic PhD programme with about 15 other students in KMi, plus peers in the Computing department and Institute of Educational Technology who together make up the OU's Centre for Research in Computing (http://crc.open.ac.uk/).

KMi sees PhD students as critical to its mission, and awards Studentships (£12,978/year tax free for 2008/09), with no additional fees, compulsory examinations or teaching required. Participation is required in CRC PhD events and thesis milestones, as specified in the KMI Research Degrees policy (http://kmi.open.ac.uk/studentships/policy.php). Additional training courses to develop your generic research skills are run across the OU, attendance at which is agreed with your supervisor.

The Open University (http://www.open.ac.uk) is UK's only distance learning university with a dedicated mission for excellence in teaching and research. PhD programmes are residential, however, and the student would carry out their research at the KMi in the Open University's central Milton Keynes campus.

Milton Keynes (http://www.mkweb.co.uk/), located in the triangle Cambridge, Oxford and London, is an exciting and vibrant place to be. It is one of the fastest growing cities in the country with fantastic shopping facilities, Xscape Snow slope, new skydiving centre and much more. Milton Keynes is also home to some major employers with Abbey National, Argos and The Open University having headquarters in the city. With more businesses continuing to locate here, unemployment levels are among the lowest in the country. Milton Keynes has excellent transport links with the M1 motorway and A5 running alongside the city and a fast train link into London Euston (35 minutes).

Applications

This studentship is available for immediate start. Applications should comprise an application form, C.V. and a proposal outlining how you would tackle this project. They should be submitted to:

Research School
The Open University
Walton Hall
Milton Keynes
MK7 6AA
UK