Design of dynamic, adaptative and context-sensitive TEL dashboards
PhD Student: Inès Dabbebi
Advisor(s): Sébastien IKSAL (LIUM-IEIAH) & Serge Garlatti (Labsticc-IHSEV)
Co-advisor(s): Jean-Marie Gilliot (Labsticc-IHSEV)
Funding: ANR Hubble Project
This thesis is part of a general problem related to technology enhanced learning (TEL) and more specifically to the construction of analysis processes to accompany the decision-making of actors involved in the teaching and learning system (teachers, learners, designers, administrators, etc.). The TEL researcher is also involved in the production of concepts, indicators or models. More specifically, we are interested in the visualization stage of this analysis process by proposing models describing the different aspects of a dashboard and a generation process to produce an adaptive, contextual and interactive dashboard for operational actors.
To define what a learning dashboard is, we use the following Schwendimann definition:”A learning dashboard is a single display that aggregates different indicators about learner (s), learning process (es), and/or learning context (s) into one or multiple visualizations”. In this definition, we note in particular the aggregation of indicators on learners, learning processes and taking into account the learning context, which corresponds to the adaptive and contextual aspects of our dashboards.
This work is part of the ANR HUBBLE project, which aims to create a national observatory for the construction and sharing of mass data analysis processes based on traces left in e-learning environments. A special feature of the project is the use of several analysis platforms, such as UTL (Usage Tracking Language), KTBS (Kernel for Trace Based System) and UnderTracks, either separately or jointly. A HUBBLE dashboard must therefore be able to integrate the visualization of indicators from these different platforms.
We have sought to identify generic dynamic, adaptive and contextual dashboard structures to meet users’ needs, which should be capitalizable and reusable to facilitate users’ work. The ensuing questions are
(i) is it possible to describe a generic dashboard, but dedicated to an observation objective?
(ii) Is context an important element in the adaptive dashboard generation?
(iii) is it possible to dynamically generate a dashboard adapted to a user and his activity?