Cognitive AI for Adaptive and Personalized Learning
Published in Computational Sciences, Behavioural Sciences & Psychology, and Education
In recent years, Artificial Intelligence has undergone a remarkable advancement in Education which has enabled it to provide significant systems capable of considering how learners think, learn, progress, and interact with educational environments far beyond content recommendation and automation toward
By considering the intersection of Artificial Intelligence, cognitive systems, and digital education as a key focus of my research, I aim to design intelligent learning environments that take into account learner behavior and evolving cognitive states. Therefore, a fundamental question guiding my work is:
How can we design intelligent educational systems that understand where learners are in their cognitive and knowledge development, and use this understanding to deliver more adaptive, tailored, and meaningful support?
From this perspective, several complementary research areas are brought together, including learner modeling, knowledge tracing, educational recommender systems, adaptive learning, cognitive load, learning analytics, and human–AI interaction.
For instance, Knowledge Tracing can be used to estimate how a learner’s knowledge matures throughout the learning process. This cognitive and behavioral information can be used to move beyond generic recommendations and toward learning activities that are more appropriate to each learner’s existing needs and level of readiness especially when integrated with recommender systems and machine learning.
Exploring how Generative AI and Large Language Models can contribute to cognitive support in learning is another area of my research interest. In lieu of considering these technologies merely as simple tools for generating content, I am interested in the way they can support learners through explanation, reflection, feedback, scaffolding, problem-solving, and personalized learning experiences.
Effective support in educational AI- which is a key challenge here- necessitates more than well-designed prompts; as it also depends on a large understanding of the learner and the learning context. This inspires me to be more interested in context engineering, where information about learner characteristics, prior knowledge, learning history, pedagogical objectives, activities, and contextual factors can be designed to lead AI systems toward more pertinent and meaningful educational interventions.
Therefore, my present work examines the integration of:
- Artificial Intelligence in Education
- Cognitive Systems
- Learner Modeling
- Knowledge Tracing
- Educational Recommender Systems
- Adaptive Learning
- Cognitive Load
- Learning Analytics
- Generative AI
- Context Engineering
- Human–AI Interaction
- Trustworthy AI
Through Springer Nature Research Communities, I look forward to sharing ideas and research perspectives with scholars exploring how AI and cognitive approaches can contribute to more adaptive, human-centered, and effective learning environments.
I am an Associate Professor of Computer Science at the École Normale Supérieure (ENS), Abdelmalek Essaâdi University, Morocco. My research interests focus on Artificial Intelligence in Education, e-learning, educational recommender systems, adaptive learning, human–computer interaction, and trustworthy AI.
I coordinate the Master’s program in E-Learning and Educational Intelligents Systems at Ecole Normale Superieure, where I teach and supervise research projects related to machine learning, emerging educational technologies, UI/UX, and intelligent learning environments. My current research explores how AI, learner modeling, knowledge tracing, recommender systems, and generative AI can support personalized and effective learning experiences.
I am also involved in doctoral training, research supervision, peer review, and international scientific conferences. I am particularly interested in interdisciplinary research connecting artificial intelligence, education, learning analytics, and digital transformation in higher education.
