ABSTRACT A competency‐based approach supported by personalized learning paths and prompt feedback accelerates skill development by continuously adapting to learners' needs and maintaining high levels of engagement. Capturing and understanding learner competency development through interaction data offers the potential for early intervention and optimized educational design, yet introduces challenges related to scalability and complexity. We present TracePath , a novel graph‐based framework that models learner trajectories as directed graphs, where nodes correspond to competencies or learner states and edges denote transitions such as validation or rejection events. This approach uncovers common learning pathways, identifies bottlenecks, and supports predictive analytics. At the core, a generic metamodel formalizes Competency Transition Graphs (CTGs), enabling comprehensive graph‐based analytics implemented over a hybrid polystore architecture that integrates both relational and NoSQL databases. Our design decouples data extraction from graph exploration, allowing efficient querying, clustering, and pattern matching to deliver timely and explainable learning insights. Empirical validation using real‐world data from the écri+ e‐certification project demonstrates TracePath's effectiveness in providing scalable, dynamic, and low‐latency learning analytics to support personalized education.

International audience

International audience

We presented in this paper a protocol for users’ needs gathering in order to study the strategies when they interact with data indicators. As we aim at proposing a design approach allowing the data indicators to be capitalized, we need to encourage the involvement of users in the design process. Their actions can be diverse, including appropriating, reusing, sharing, and adapting data indicators. This led us to set up focus groups including heterogeneous and non-expert users in these complex activities. The protocol, based on a gamification methodology, allows us to initiate a user-centered design approach for our proposal. The collected verbatim will then be analyzed to extract different expressions of the users’ needs for data indicators, as well as their needs in terms of interaction with the latter. The first iterations of the protocol have enabled us to establish our research directions and put our research effort in perspective.

International audience

International audience

International audience

International audience

Researchers have proven with both theoretical and empirical studies that technologies could enhance learning. Meanwhile, technologies could also create barriers to the latter. Particularly, when the use of technologies causes security and privacy concerns, E-learning becomes less fruitful as the participants are too afraid to be exposed by what has been provided to help them learn in the first place. This paper presents a study on user's perception in using E-learning technologies and the relevant issues. The major contribution of this paper is the awareness-raising of security and privacy issues, which are often overlooked in the research efforts that implicate user tracking and personal data usage for instructional purposes.

This paper presents an approach for closely observing the different levels of Human and Computer Interactions during student’s communication activities on Computer Mediated Communication (CMC) tools. It focuses on how to efficiently track learners’ activities, along with their outputs, and to exploit the collected tracking data in order to assist participants, both learners and teachers, in the learning process. Three experiments using the system and the result analysis are also presented.

Tracking data of user's activities resulting from computer mediated communication (CMC) tools (forum, chat, etc.) is often carried out in an ad-hoc manner, which either confines the reusability of data in different purposes or makes data exploitation difficult. Our research works are biased toward methodological challenges involved in designing and developing a generic system for tracking user's activities while interacting with asynchronous communication tools like discussion forums. We present in this paper, an approach for building a Web-based system for observing and analyzing user activity on any type of discussion forums