Main research interests
- Technology Enhanced Learning
- Learning Analytics: Tracking data, Data Indicators, Data Analysis and Visualization, Data Mining
- Réalité Mixte
- Human-Computer Interaction
- User Experience (UX)
- Serious Games
- Web Intelligence and Interactive systems
(Since March 2021)
Enhancing Situated learning with Collaborative Games and Mixed reality
Work package 3: Innovative Augmented Reality Interaction to Support Collaboration.
(Since October 2018)
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PASTEL (Transcription Automatique de la Parole pour l’Apprentissage et la Formation)
Along with the democratization of increasingly high-performance digital and communication technologies, higher education and training for adults are constantly challenged by both the renewal and the adaptation of teaching practices. While the frontiers between guided learning and self-learning are becoming less obvious, which tends to redefine the role of the teacher and the learner, the great accessibility of technologies, on the other hand, enables a diversity of interaction modes between teachers and learners, as well as between learners and learners.
We believe that the widespread use of digital technologies, especially online courses starts with the development of SPOC (Small Private Online Courses) at a reduced cost while capable of largely covering numerous educational areas. For that matter, the engineering process needs to better involve teachers in charge of the lectures, and to allow them to personalize their content and teaching methods in order to develop blended learning, thus the entanglement of the use of digital content and classroom teaching.
PASTEL is a research project that aims to explore the potential of real time and automatic transcriptions for the instrumentation of mixed educational situations where the modalities of the interactions can be face-to-face or online, synchronous or asynchronous. The speech recognition technology approaches a maturity level that allows new opportunities of instrumentation in pedagogical practices and their new uses. More specifically, we develop (1) a real-time transcription application, and (2) educational outreach applications based on the transcription system outputs. We will use these results to automatically generate the materials of a basic SPOC. A set of editing features will be implemented for the mentioned applications that will allow the teacher to adapt and customize these contents according to their needs. Then, the developed applications will be made available to public institutions for higher education and research, and will also be transferred to the industry through Orange or start-ups associated to the research laboratories involved in the project.
The major innovations of PASTEL cover the discourse structure from automatic transcriptions that are linked to its educational objectives. The innovation also features the challenging flow processing in real time, which is required when the discourse structure is being used in a face-to-face situation. The project also brings innovative solutions in terms of instrumentation, and diversification of pedagogical practices, as well as a new approach to design and structure online educational contents, based on the use of speech recognition technology.
HUBBLE (Human Observatory Based on Analysis of e-Learning Traces
The HUBBLE project (HUman oBservatory Based on anaLysis of eLEarning traces) is funded by the French Agency of Research (ANR). It aims at proposing the creation of an observatory for building and sharing analysis processes of massive elearning traces. HUBBLE will enable the participants (teachers, students, learning designers, managers, etc.) to analyze and explain learning and teaching phenomena with technology enhanced learning environments. The analysis processes will guide the decision-making of the participants involving in the learning and teaching setting.
The HUBBLE project aims at promoting collaborative research activities between research teams in Computer Sciences and also in Human and Social Sciences, thus developing a national observatory. The research activity is based on case studies proposed by partners. Beyond the experimental or technological results, this project fosters and strengthens a national community around Learning Analytics with an objective to increase its visibility inside the European and international research communities.
Contextual Data Indicators on Mobile Devices
(Since September 2013)
This research project covers two important aspects regarding tracking data analysis and visualization. First, the data analysis process will be made in a context where a tracking system evolves and adapts accordingly to how an activity is being carried out and how it impacts the whole learning process. Second, the data visualization will be conducted on a variety of mobile devices. Our goal is to achieve a visualization tool with dynamic and flexible user interface, thus enabling a better visualization of data indicators on mobile devices as well as a more pertinent analysis of the information featured each data indicator.
Massive Online Serious Gaming (Cibus)
(September 2011 – may 2012)
Cibus is a Serious Game that aims at enhancing learning process by introducing new simulation tools to the players (i.e. learners), helping them develop new skills and approaches in business/company creations. The game also places social interactions at the center of the players’ activities, thus inciting them to collaborate more efficiently with the support of computer-mediated communication tools, specially designed for collaboration enhancement.
A tracking approach is used to observe both the interactions and the outcomes of the players. The tracking data issued from the use of Cibus and the collaboration process will be exploited by the researchers in various contexts.
Key words: Serious Game, Elearning, Data Analysis, Tracking Data, Data Visualization, Computer-Mediated Communications
Technology Enhanced Learning
A part of my research efforts has been put into the improvement of technologies that better support the learning process. More precisely, I am interested in using technological approaches to enhance the participation and interactivity in e-learning. For instance, I am using a tracking system to observe the communication activities among the participants throughout the learning process. The collected data will be later exploited to assist:
- tutors in student monitoring and evaluation
- learners in self-monitoring and in making self-assessment.
My research work also covers other issues related to the use of tracking data in e-learning:
- data collection: how can we collect data with fine granularity, containing substantial information to describe both the process and the outcome of an activity?
- data structuring: how can we represent data to make it usable in different tools?
- data exploitation: how can we analyze and visualize tracking data?
Key words: Learning Process, Distance Learning, Human learning, Computer-Mediated Communication, Tracking System, Data Indicators
I work on different research projects related to Game based learning, including Learning Game Factory (LGF) and MyLogistic Serious Game. I strongly participate in the latter, which aims at providing a technological solution to enhance a logistic training course.
MyLogistic Serious Game places an emphasis on both the design and development of Serious Games to allow users to:
- discover various aspects of the logistic activities
- follow a training course where their activities are guided by learning scenario, specifically designed by both researchers specialized in e-learning and experts from the logistics industry.
Key words: serious game, supply chains, data warehouse, course management system
- Study different types of actions and interactions of a user activity on Computer-Mediated settings (E-learning platform, CMS, CMC tools, etc.).
- Create interactive computerized systems to support the participants in the learning process.
Key words: Human-Computer Interaction (HCI), User action, Computer Action, Human-Human Interaction Mediated by Computer, Computer-Computer Interaction
Design and develop TrAVis (Tracking data analysis and Visualization tools) to enable users to
- Manipulate the tracking data (data storage, modification, …)
- Analyze the tracking data (computing statistical data, generating synthetic information from tracking data, …)
- Visualize the tracking data in graphical representations
Key words: data analysis, data visualization, data processing, interaction analysis, data indicator
Design and implementation of Web Service for Contextual Discussion Forum for E-Learning platforms:
- Setting up n-tier architecture based on Web Service for multiple learning platforms
- Data exchange over Web Service
Key words: Web Service