Learning analytics and dashboards for tablet-based active learning in classroom
Profile of the candidate: PhD in one of the following research areas: e-learning, data visualisation, data science. Good skills in web programming and data analysis. Interest for interdisciplinary research (interaction with psychologists).
Project Description. Expectations and experiences of today’s students seem to diverge increasingly from the traditional teaching practices. In a large classroom, student-teacher interactions are rare, and students are more spectators than actors during the lecture being taught. Similarly, teachers cannot assess understanding and real-time assimilation of their lectures by students. The aim of eFIL project is to go beyond ‘classical’ active learning methods to improve learning in higher education using and evaluating a new digital learning environments. CAMIA is a workbook designed for active learning in higher education during face-to-face lectures that was designed and developed during the last 2 years by the INSA Rennes IntuiDoc team.
The eFIL project regroups the following partners:
The LP3C team (Université de Rennes 2) that will provide expertise in cognitive psychology, social psychology, psychology of education, and ergonomics.
The Intuidoc team (IRISA Laboratory) that will provide expertise in Human-Document Interactions by associating the issues of the fields of Pattern Recognition and Human-Machine Interaction.
The DUKe research group (LS2N Laboratory) that will provide expertise in data mining, privacy expert knowledge and user interactions through adapted visual supports.
The Duke team will mainly focus on one work package that regroups all eFIL trace-related work:
trace modelling and collection for various version of CAMIA
trace analysis and mining, so as to define insightful trace-based indicators
trace visualisations and trace-based asynchronous & synchronous dashboards for researchers and instructors.
while also participating to the design and the evaluation of the tools with the partners.
Duration: 24 months, beginning Fall 2017.
Workplace: LS2N UMR 6004 CNRS, Polytech Nantes (graduate engineering school of University of Nantes). Some travels to Rennes are to be expected.
Salary: > 2000€ net, depending on experience and qualification