Madjid SADALLAH

Ph.D., Researcher - Engineer

Short Bio

I am a computer scientist with a robust foundation in both theoretical and applied aspects of the field. I hold a PhD in Computer Sciences from the University Abderrahmane Mira (Bejaia, Algeria), an Engineer degree in Computer Sciences from the University of Science and Technology USTHB (Algiers, Algeria), and a Magister degree in Computer Sciences from the University Abderrahmane Mira. My academic journey has led me to various research roles, each enriching my understanding and expertise.

Currently, I am serving as a postdoctoral researcher at LIRIS, specifically within the TWEAK team. Here, I am part of the MOBILES project that aims to understand and support the spatial practices of international students in France. Using advanced analytics, I strive to comprehend the temporal and spatial behavior of these students and generate recommendations. This work is not merely aimed at enhancing learning experiences, but also at uncovering potential opportunities and diversifying students’ practices.

Before joining LIRIS, I was a research engineer at IMT Atlantique in Brest, France. During my tenure there, I was part of the MOTEL research team. My work involved a blend of theoretical research and practical application, resulting in the development of innovative analytical tools and models that aimed to enhance the way we understand and support digital learning practices. I also spearheaded several key projects, each with its unique challenges and breakthroughs, contributing to the field of learning analytics. These projects ranged from designing effective Learning Analytics Dashboards (LADs) that support sensemaking and decision making, to developing methods for collecting and analyzing data, and devising models to evaluate ongoing learning paths.

Earlier in my career, I served as a full-time permanent researcher (Maître de Recherche B) at the Algerian Research Center on Scientific and Technical Information CERIST. My research at CERIST was multifaceted and involved various research projects. My primary focus was on structured documents, learning analytics, educational data mining, and the application of Artificial Intelligence to online learning. This involved developing and implementing advanced algorithms and models to analyze and interpret complex educational data. The goal was to uncover insights that could enhance online learning practices and improve educational outcomes. This experience has greatly enriched my understanding of the intersection between computer science and education, and continues to inform my current research endeavors.

View my academic CV (in French)

Research topics

My current research primarily focuses on the intersection of Learning Analytics, Educational Data Mining, and Artificial Intelligence in Education. Key areas of interest include:

  • Human-Computer Interaction (HCI): Exploring ways to enhance the interaction between humans and computers in educational settings.

  • Technology-Enhanced Learning (TEL): Leveraging technology to create more effective and engaging learning environments.

  • Design and Co-Design of Analytics Tools: Developing and refining tools for analyzing educational data, often with the involvement of end-users.

  • Knowledge Engineering: Investigating methods to capture, represent, and apply knowledge in educational contexts.

  • Artificial Intelligence in Education (AIED): Harnessing AI techniques to personalize and optimize the learning experience.

  • Digital & Multimedia Document Reengineering: Transforming digital content and multimedia resources to better support education.

  • Hypermedia and Hypervideo Systems: Studying the use of hypermedia and hypervideo technologies in educational content and delivery.

These areas constitute the core of my research focus, driving my efforts to advance educational practices and technology.