Towards an Intelligent Tutoring System for Logical Reasoning in Multiple Contexts. - Roger Nkambou; Janie Brisson; Clauvice Kenfack; Serge Robert; Pamela Kissok; Ange Tato (EC-TEL, 2015)

A Bayesian Network for the Cognitive Diagnosis of Deductive Reasoning. - Ange Tato; Roger Nkambou; Janie Brisson; Clauvice Kenfack; Serge Robert; Pamela Kissok (EC-TEL, 2016)

Predicting Learner's Deductive Reasoning Skills Using a Bayesian Network. - Ange Tato; Roger Nkambou; Janie Brisson; Serge Robert (AIED, 2017)

Convolutional Neural Network for Automatic Detection of Sociomoral Reasoning Level. - Ange Adrienne Nyamen Tato; Roger Nkambou; Aude Dufresne (EDM, 2017)

Semi-Supervised Multimodal Deep Learning Model for Polarity Detection in Arguments. - Ange Tato; Roger Nkambou; Aude Dufresne; Claude Frasson (IJCNN, 2018)

Predicting Emotions From Multimodal Users' Data. - Ange Tato; Roger Nkambou; Claude Frasson (UMAP, 2018)

Hybrid Deep Neural Networks to Predict Socio-Moral Reasoning Skills. - Ange Adrienne Nyamen Tato; Roger Nkambou; Aude Dufresne (EDM, 2019)

Using EEG Features and Machine Learning to Predict Gifted Children. - Ramla Ghali; Ange Tato; Roger Nkambou (FLAIRS, 2019)

Some Improvements of Deep Knowledge Tracing. - Ange Tato; Roger Nkambou (ICTAI, 2019)

Predicting Subjective Enjoyment of Aspects of a Videogame from Psychophysiological Measures of Arousal and Valence. - Julien Mercier; Pierre Chalfoun; Matthew Martin; Ange Adrienne Nyamen Tato; Daniel Rivas (ITS, 2019)

Towards Predicting Attention and Workload During Math Problem Solving. - Ange Tato; Roger Nkambou; Ramla Ghali (ITS, 2019)

Improving First-Order Optimization Algorithms (Student Abstract). - Ange Tato; Roger Nkambou (AAAI, 2020)

Using AI Techniques in a Serious Game for Socio-Moral Reasoning Development. - Ange Tato; Roger Nkambou; Aude Dufresne (AAAI, 2020)

Learning Logical Reasoning : Improving the Student Model with a Data Driven Approach. - Roger Nkambou; Janie Brisson; Serge Robert; Ange Tato (ITS, 2021)

Ontological Reference Model for Piloting Procedures. - Marc-Antoine Courtemanche; Ange Tato; Roger Nkambou (ITS, 2022)

Deep Knowledge Tracing on Skills with Small Datasets. - Ange Tato; Roger Nkambou (ITS, 2022)

Towards Adaptive Coaching in Piloting Tasks: Learning Pilots' Behavioral Profiles from Flight Data. - Ange Tato; Roger Nkambou; Gabrielle Joyce Nana Tato (ITS, 2022)

Infusing Expert Knowledge Into a Deep Neural Network Using Attention Mechanism for Personalized Learning Environments. - Ange Tato; Roger Nkambou (Frontiers Artif. Intell., 2022)

Learning Logical Reasoning Using an Intelligent Tutoring System: A Hybrid Approach to Student Modeling. - Roger Nkambou; Janie Brisson; Ange Tato; Serge Robert (AAAI, 2023)

Towards Extracting Adaptation Rules from Neural Networks. - Ange Tato; Roger Nkambou (AIED (Posters/Late Breaking Results/...), 2023)

Introduction to Neural Networks and Uses in EDM. - Agathe Merceron; Ange Tato (EDM, 2023)

Towards a multi-modal Deep Learning Architecture for User Modeling. - Ange Tato; Roger Nkambou (FLAIRS, 2023)

Automatic Execution of the Ontological Piloting Procedures. - Marc-Antoine Courtemanche; Ange Tato; Roger Nkambou (ITS, 2023)

Automatic Learning of Piloting Behavior from Flight Data. - Ange Tato; Roger Nkambou; Gabrielle Joyce Nana Tato (ITS, 2023)

Integrating an Ontological Reference Model of Piloting Procedures in ACT-R Cognitive Architecture to Simulate Piloting Tasks. - Guy Carlos Tamkodjou Tchio; Marc-Antoine Courtemanche; Ange Adrienne Nyamen Tato; Roger Nkambou; Valéry Psyché (ITS, 2023)

Towards Cognitive Coaching in Aircraft Piloting Tasks: Building an ACT-R Synthetic Pilot Integrating an Ontological Reference Model to Assist the Pilot and Manage Deviations. - Guy Carlos Tamkodjou Tchio; Roger Nkambou; Ange Adrienne Nyamen Tato; Valéry Psyché (ITS (1), 2024)

Handling of Abnormal Aircraft Takeoff Procedures: Cognitive Modeling of an ACT-R Synthetic Pilot Integrating an Ontological Reference Model. - Guy Carlos Tamkodjou Tchio; Roger Nkambou; Ange Adrienne Nyamen Tato; Valéry Psyché (NiDS, 2024)

Can LLMs Generate Accurate Bayesian Networks to Enhance Knowledge Tracing ? - Ange Tato; Roger Nkambou (AIED (3), 2025)

Towards Predicting Complex Carpooling Trajectories with Context-Augmented BERT-LLM in Chaotic Environments. - Daril Kengne; Roger Nkambou; Ange Tato; Clara Lacourarie (IEA/AIE (1), 2025)

Leveraging LLMs for Bayesian and Deep Knowledge Tracing in the Logic-Muse Intelligent Tutoring System. - Ange Tato; Roger Nkambou (ITS (1), 2025)

Enhancing Pilot Training and Decision-Making Using Ontologies: A Cognitive Assistance Approach. - Guy Carlos Tamkodjou Tchio; Roger Nkambou; Valéry Psyché; Ange Adrienne Nyamen Tato (ITS (1), 2025)