What I do

My research interests include Human-Computer Interaction, Information Visualization and Data Analysis, User Experience Modeling, Reflective technologies, Interpretation systems, or Document and Knowledge Engineering. Application domains are related to education, culture, health, humanities… I focus on interdisciplinary approaches for the study of human-machine coupling and co-development and collaborate with people from sociology, psychology, ergonomy, anthropology, education science, philosophy, design, medecine, focusing on real world activities.

News (all)

Nov. 20: Postdoc in France (12 months, possibly 18 months) - Executive Function testing in Virtual Reality. Within an ongoing collaboration between and Nantes Universities, Hanyang and Nantes University Hospitals, on the use of VR environments for the testing of executive functions in VR, the candidate will design and develop a new integrated VR environment, design an experimental protocol that will be run both in France and Korea. (more info)

Jan. 20: Postdoc in Korea and France - Executive Function testing in Virtual Reality (18 months). The candidate will participate to the definition of several experimental evaluations of VR environments for executive functions testing, both in Korea and France, conduct experiments, analyze the resulting quantitative and qualitative data. and publish with the team members. (more info)

Nov. 19: Postdoc position in Immersive Analytics (6-7 months from Jan. 202O). The candidate will extend the work we have been carrying on how to visualize and interact with 3D scatterplots in Virtual Reality. His/her first task is to develop an experiment that aims to compare two types of data immersion. Other tasks and research directions will depend on personal interest of the candidate. (more info)

Recent publications (all)

Madjid Sadallah, Benoît Encelle, Azze-Eddine Maredj, Yannick Prié. (2020) Towards fine-grained reading dashboards for online course revision in Educational Technology Research and Development, 22p doi Show abstract Providing high-quality courses is of utmost importance to drive successful learning. This compels course authors to continuously review their contents to meet learners’ needs. However, it is challenging for them to detect the reading barriers that learners face with content, and to identify how their courses can be improved accordingly. In this paper, we propose a learning analytics approach for assisting course authors performing these tasks. Using logs of learners’ activity, a set of indicators related to course reading activity are computed and used to detect issues and to suggest content revisions. The results are presented to authors through CoReaDa, a learning dashboard empowered with assistive features. We instantiate our proposals using the logs of a major European e-learning platform, and validate them through a study. Study results show the effectiveness of our approach providing authors with more awareness and guidance in improving their courses, to better suit learners’ requirements.

Madjid Sadallah, Benoît Encelle, Azze-Eddine Maredj, Yannick Prié. (2019) Leveraging Learners’ Activity Logs for Course Reading Analytics Using Session-Based Indicators in International Journal of Technology Enhanced Learning, 12 (1) doi Show abstract A challenge that course authors face when reviewing their contents is to detect how to improve their courses in order to meet the expectations of their learners. In this paper, we propose an analytical approach that exploits learners’ logs of reading to provide authors with insightful data about the consumption of their courses. We first model reading activity using the concept of reading-session and propose a new and efficient session identification. We then elaborate a list of indicators computed using learners’ reading sessions that allow to represent their behaviour and to infer their needs. We evaluate our proposals with course authors and learners using logs from a major e-learning platform. Interesting results were found. This demonstrates the effectiveness of the approach in identifying aspects and parts of a course that may prevent it from being easily read and understood, and for guiding the authors through the analysis and review tasks.

Rubiela Carrillo, Yannick Prié, Élise Lavoué. (2019) Observing Learner Engagement on Mind Mapping Activities Using Learning Analytics in ECTEL 2019, European Conference on Technology Enhanced Learning, Delft, Netherlands, Sept 2019. pp. 668-672 doi Show abstract Research on learner engagement has increased in recent years arguing that it favors academic success. Teachers want their learners to engage in meaningful learning activities, like mind mapping, but they lack clues for observing their engagement along the activity. In this paper, we propose indicators of behavioural and cognitive dimensions of learner engagement for mind mapping activities based on interaction traces. Our indicators have been defined from final mind maps as well as from the mind mapping processes. We discuss implications for the observation of learner engagement in learning activities similar to mind mapping.

Adrien Fonnet, Yannick Prié. (2019) Survey of Immersive Analytics in IEEE Transactions on Visualization and Computer Graphics, 22 pp. doi Show abstract Immersive analytics (IA) is a new term referring to the use of immersive technologies for data analysis. Yet such applications are not new, and numerous contributions have been made in the last three decades. However, no survey reviewing all these contributions is available. Here we propose a survey of IA from the early nineties until the present day, describing how rendering technologies, data, sensory mapping, and interaction means have been used to build IA systems, as well as how these systems have been evaluated. The conclusions that emerge from our analysis are that: multi-sensory aspects of IA are under-exploited, the 3DUI and VR community knowledge regarding immersive interaction is not sufficiently utilised, the IA community should focus on converging towards best practices, as well as aim for real life IA systems.