D. STELLAR Incubator
Incubators are targeted at early-stage researchers. The idea is to support promising researchers with mobility or “incubation” scholarships to spend up to few months in another influential laboratory or research centre to foster integration and the establishment of close relationships. This instrument will support cross-fertilisation while working collaboratively on selected exploratory research actions.
STELLAR is launching an Incubator Programme, aimed at supporting promising early career researchers with mobility or “incubation scholarships” to spend some months in another research institution or enterprise with the aim of either fostering the incubation of new ideas/projects, or exploiting new prototypes/services/approaches.
An Incubator must involve:
- an early career researcher (not in his/her early PhD stages), who is interested in a topic/idea/prototype relevant in the field of TEL
- a host institution, interested in the same topic/idea/prototype.
It is a necessary condition that the host institution and /or the junior researcher are within STELLAR.
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
- 4 proposals for Incubators received
- 3 of the proposals are from non-STELLAR partners to visit a STELLAR institution, the 4th the other way round
Selected Incubators
After the evalaution and selection process the following Incubator has been approved and funded:
| Incubator Title | Person & Institution | Host Institution |
| CoMoCo - Combining Gaze data with audio and action logs to build a computational model of collaboration quality | D. Diziol (University of Freiburg) | EPFL (c/o Prof. P. Jermann) |
CoMoCo Incubator - Combining gaze data with audio and action logs to build a computational model of collaboration quality
The proposed Incubator addresses one of the major challenges in the area of TEL, more specifically in the area of computer-supported collaborative learning: the dilemma of providing too little structure to students’ interaction on the one hand and overscripting collaboration on the other hand. Adaptive collaboration support is regarded as a possible solution. However, the development of adaptive support is difficult as it is necessary to define and assess meaningful indicators for the quality of students’ collaboration.
This Incubator proposes the development of a computational model based on action, audio and gaze data: First, we will develop an interaction model to assess collaboration quality based on dialogue (rating scheme); then, we will use machine learning techniques to find indicators in students’ actions and gaze that can predict the collaboration quality as assessed with the interaction model. As these indicators can be measured automatically during students’ ongoing collaboration, the computational model will enable the implementation of adaptive collaboration support.
The Incubator particularly benefits from the interdisciplinary background of the submitters: the expertise of the Junior Researcher lies in the analysis of student dialogue; the expertise of the Host Institution lies in the analysis of dual gaze data. The output of the proposed Incubator will be a conference contribution and a joint publication on the developed computational model, and possibly a presentation of the model in a workshop of the linked Theme Team.
For more details on the Call, please click here.