C. STELLAR Theme Teams
STELLAR will support a targeted team building programme to produce a set of Grand Challenge focused, short-term new team interactions instigated by mid-career researchers. These teams will be established to collaboratively explore and analyse emerging research topics that have been identified by the Grand Challenge framework. The idea of supporting and bringing out this group of researchers reflects a serious European capacity problem in the middle tier of research staff.
STELLAR Theme Team is a network of mid-career researchers from different institutions, whose aim is to explore and analyze collaboratively emerging research topics in the field of TEL. A Team may be a completely new network created around a specific topic of common interest, or composed of researchers who have already worked together on a certain issue (e.g. at a workshop or within a longer project).
The mission of a Theme Team is to share and integrate competences, methodologies and ideas already developed. The Teams are a means to integrate European research units in the field of TEL, but also competences coming from entreprises and institutions not included in the STELLAR network.
Within STELLAR two Calls for proposals are foreseen. The First Call was launched in December 2009 and closed on January 15th 2010. The next Call is foreseen in Autumn 2010.
Figures from the First Call for proposals:
- 21 proposals for Theme Teams received
- 86 institutions were from outside STELLAR (which is 73,5%)
- 31 institutions were from STELLAR (which is 26,5%)
- 13 (out of the 21 proposals) were lead by a non-STELLAR partner (62%)
Selected Theme Teams
After the evaluation and selection process the following Theme Teams have been selected and funded:
| TT Title | TT Leader | Partners involved |
| SRLinTELEs - Self-regulated learning in technology enhanced learning environments | University of Köln (DE) | Fernfachhochschule Schweiz; Nottingham Trent University; Vrije Universiteit Amsterdam; Universidade Católica Portuguesa; Universitat de Barcelona; CNR-ITD |
| MUPEMURE - Multiple Perspectives on Multiple Representations | Universiteit Twente (NL) |
Eberhard Kars Universität Tübingen; Nanyang Technological University; Fondation Formation Universitaire à Distance, Suisse; Albert-Ludwigs-Universität Freiburg |
| NTEL - Neuroscience, technology and the Enhancement of Learning | University of Bristol (UK) |
Universiteit Twente; University of Bristol; CNR-ITD; Katolieke Universiteit Leuven |
| Orchestrating Technology Enhanced Learning in Future Learning Spaces | Virginia Polytechnic Institute and State University (USA) |
Finnish Institute for Educational Research; Ghent University; Futurelab; LMU |
| DATATEL - A Data Set Framework for Recommender Systems in Technology Enhanced Learning | Open University of the Netherlands (NL) |
European Schoolnet; Greek research and Technology Network; FIT Fraunhofer; Open University of the Netherlands; Katolieke Universiteit Leuven; Know Center |
SRLinTELEs - Self-regulated learning in technology enhanced learning environments
Political and economic pressures have created a strong motive for transforming the experience of teaching and learning. New technologies offer an infrastructure within which this can be made to happen. Using these new technologies effectively requires self-regulated learning (SRL); on the other hand, technology enhanced learning environments (TELEs) have also shown the potential to foster the development of SRL. It is therefore highly desirable to study SRL in TELEs within the framework of the STELLAR Grand Challenges.
Issues related to SRL in TELEs will be explored in the Theme Team and discussed with other researchers, educators and politicians at an international conference to take place in Cologne / Germany. Conference results will be made available as an edited book and on the STELLAR Open Archive. The main results of the Theme Team will also be disseminated and discussed at international conferences and with STELLAR members by presenting them at one or more of the following STELLAR initiatives: the Alpine Rendez-Vous, the STELLAR Winter-School, the STELLAR Summer-School and through the TEL-Europe portal. A website with the results will remain open for comments from other researchers, as basis for future works.
The relationship between SRL and TELE is a new field of inquiry which has produced interesting results, showing the potential to provide innovative solutions to the need for SRL development in TEL.
MUPEMURE - Multiple Perspectives on Multiple Representations
Our understanding of the exact sciences, such as mathematics, physics, biology etc., and phenomena and topics such as statistics, photosynthesis, the water cycle, etc. is strongly evoked and guided by how these topics are graphically or textually represented in text books or online environments. To foster active elaboration of science topics juxtaposing multiple representations is not enough. Beyond current multimedia learning research, the MUPEMURE Theme Team investigates how learners can be facilitated to actively share, process and acquire multiple perspectives on multiple representations of mathematical and science topics. We combine latest technology for creating, modifying, and sharing representations in CSCL scenarios with group awareness and scripting approaches.
The technological advances include intelligent tools that can cluster and analyze components of multiple representations and provide feedback adapted to learners’ advancing knowledge (awareness approach). Moreover, MUPEMURE investigates approaches to guide learners to construct, compare, and follow-up on peers’ multiple knowledge representations (scripting approach). Sharing multiple perspectives on multiple representations (MUPEMURE) can affect the course and type of learners’ reasoning by disambiguating discourse, fostering self-explanation and elaboration, and by strengthening a shared task focus.
MUPEMURE aims to attain empirical results focusing on processes of actively working with and elaborating on multiple representations with latest technology in mash-up environments as well as focusing on learning outcomes including multi-perspective knowledge. The output of the Theme Team will be at least one symposium at an international conference such as CSCL and following up on that a special issue in an ISI-journal such as JLI.
NTEL - Neuroscience, Technology and the Enhancement of Learning
Burgeoning insights in the sciences of mind and brain are generating fresh perspectives on education. The impact of such insights may be greatest where another force for change, technology, is already transforming learning. However, to date, little work has focused specifically on the potential of the neurosciences to inform the design and use of technology in education. The role of brain science in understanding developmental disorders is now well-established but, since all learning possesses biological substrates, there is a strong justification for the potential importance of neurobiological perspectives within educational contexts in general.Recent advances include improved understanding of attention, memory, meaning, gender differences, creativity, language acquisition, mathematical development, motivation and many other areas of direct relevance to learning with technology. Neuroscience and educational technology are two rapidly developing fields of enterprise and, at their confluence, there is now a rapidly increasing need for innovative theorising and the development of improved research capacity. The proposed theme team aims to meet this need.
Orchestrating Technology-Enhanced Learning in Future Learning Spaces
The Theme Team gathers expertise in research, development, and assessment to generate knowledge on pedagogical interventions to successfully orchestrate learning in future learning spaces.
The Theme Team will produce the following results:
- Identification of roles and relationships of participants and tools involved in different learning contexts: physical, distributed, formal and informal
- Definition of a systematic theoretical framework for orchestrating learning in different settings, drawing on emerging topics in situated/collaborative/mobile learning and distributed/situated cognition, including a review of innovative pedagogies
- Analyses of how existing technologies could support practitioners and more knowledgeable others in orchestrating learning, resulting in a taxonomy of tools to support practical implementation and assessment of orchestrated learning.
The Theme Team will define an agenda to initiate and expand scholarship and research on “orchestrating learning,” leading to the following outputs:
- A white paper and online resource for collecting empirical studies of orchestrated learning
- A conference symposium proposal
- An outline of a special journal issue to be published in 2011
It is anticipated that natural by-products of this collaboration (beyond the current grant cycle) will include grant proposals to funding agencies in the US, UK, and EU, and a coordinated research and teaching network for wider dissemination amongst practitioners and doctoral students.
The Theme Team gathers experts from diverse theoretical, institutional, and geographical domains that have impressive records of empirical research for mid-career researchers. The formation of the Theme Team will leverage this synergy to make significant contributions to TEL on a global scale.
DATATEL - A Data Set Framework for Recommender Systems in Technology Enhanced Learning
Personalisation is a key approach to overcome the plethora of information in the Knowledge Society. It is expected that personalised learning has the potential to reduce delivery costs, create more effective learning environments and experiences, accelerate time to competence development, and increases collaboration between learners. One of the promising technologies to support people to find most suitable information and peer learners are recommender systems. Recommender systems are increasingly applied in TEL in order to personalise learning content and connect suitable peer learners according to their context (individual needs, preferences, and learning goals).
There is a lot of research conducted on recommender systems in TEL but they lack standardised ways to evaluate the performance of different recommendation systems. In order to bring the research on TEL related recommender systems on a higher level benchmarks for their development are needed. These benchmarks require:
- A collection of public available data sets ranging from formal to non-formal learning settings,
- An overview of the research results of certain recommendation technologies on particular data sets,
- A common approach to evaluate recommender systems in thedomain of TEL.
The output of the Theme Team is to foster standardised benchmarks for the development of recommender systems by collecting data sets, create uniform evaluation procedures, and develop an overview method to monitor how different algorithms perform on certain data sets. The outcomes of this work will be presented at the 4th SIRTEL workshop (Social
Information Retrieval for Technology-Enhanced Learning) at the EC-TEL 2010.