4 PhD graduated (Supervision / Co-supervision)

• NEBEL Leo : Analyse de production textuelles d'élèves pour soutenir le développement des capacités rédactionnelles
• QUELENNEC Katia : Évaluation de représentations de données d'apprenants à l'aide des “learning analytics” et comparaison de leurs modalités de diffusion pour favoriser l'apprentissage
• SERGENT Thomas : Détection et constitution de groupes pour l'apprentissage de la lecture
• VERGER Mélina : Multi-criteria analysis of algorithmic fairness in artificial intelligence for education

4 PhD graduated 2014 - 2021

2010-2024 Publications

• 2024
  • Th. Sergent, M. Daniel, F. Bouchet, Th. Carron : “How Can Self-Evaluation and Self-Efficacy Skills of Young Learners be Scaffolded in a Web Application?”, IEEE Transactions on Learning Technologies, vol. 17, pp. 1184-1197, (Institute of Electrical and Electronics Engineers) (2024)
• 2023
  • M. Verger, Ch. Fan, S. Lallé, F. Bouchet, V. Luengo : “A Fair Post-Processing Method based on the MADD Metric for Predictive Student Models”, 1^st International Tutorial and Workshop on Responsible Knowledge Discovery in Education (RKDE 2023) at ECML PKDD 2023, Turino, Italy (2023)
  • M. Verger, S. Lallé, F. Bouchet, V. Luengo : “Is Your Model "MADD"? A Novel Metric to Evaluate Algorithmic Fairness for Predictive Student Models”, Proceedings of the 16^th International Conference on Educational Data Mining, Bengaluru, India, (ISBN: 978-1-7336736-4-8) (2023)
  • M. Verger, F. Bouchet, S. Lallé, V. Luengo : “Caractérisation et mesure des discriminations algorithmiques dans la prédiction de la réussite à des cours en ligne”, EIAH2023 : 11^e Conférence sur les Environnements Informatiques pour l'Apprentissage Humain, Brest, France (2023)
  • K. Oliver‑Quelennec, F. Bouchet, Th. Carron, C. Pinçon : “Usages dans le temps d’un tableau de bord d’apprentissage dans un jeu sérieux”, EIAH2023 : 11^e Conférence sur les Environnements Informatiques pour l'Apprentissage Humain, Brest, France, pp. 256-261, (Association des Technologies de l’Information pour l’Education et la Formation) (2023)
• 2022
  • K. Oliver‑Quelennec, F. Bouchet, Th. Carron, C. Pinçon : “Evaluating the Transposition of a Learning Analytics Dashboard Co-design Tangible Tool to a Digital Tool”, chapter in Open and Inclusive Educational Practice in the Digital World, Cognition and Exploratory Learning in the Digital Age, pp. 115-133, (Springer International Publishing), (ISBN: 978-3-031-18512-0) (2022)
  • Th. Sergent, M. Daniel, F. Bouchet, Th. Carron : “Détection de déficits d’autoévaluation et d’auto-efficacité et remédiation dans un EIAH”, STICEF (Sciences et Technologies de l'Information et de la Communication pour l'Éducation et la Formation), vol. 29 (2), pp. 155-184, (ATIEF) (2022)
  • K. Oliver‑Quelennec, F. Bouchet, Th. Carron, K. Fronton Casalino, C. Pinçon : “Adapting Learning Analytics Dashboards by and for University Students”, Educating for a New Future: Making Sense of Technology-Enhanced Learning Adoption, vol. 13450, Lecture Notes in Computer Science, Toulouse, France, pp. 299-309, (Springer International Publishing), (ISBN: 978-3-031-16290-9) (2022)
  • R. Chaker, F. Bouchet, R. Bachelet : “How do online learning intentions lead to learning outcomes? The mediating effect of the autotelic dimension of flow in a MOOC”, Computers in Human Behavior, vol. 134, pp. 107306, (Elsevier) (2022)
  • C. Morais Canellas, F. Bouchet, Th. Arribe, V. Luengo : “Learning Analytics Metamodel: Assessing the Benefits of the Publishing Chain’s Approach”, 13^th International Conference on Computer Supported Education, CSEDU 2021, vol. 1624, Communications in Computer and Information Science, Virtual event, France, pp. 97-114, (Springer International Publishing) (2022)
  • K. Oliver‑Quelennec, F. Bouchet, Th. Carron, C. Pinçon : “Understanding online collaboration through speech acts associated to Belbin profiles”, CSCL 2022 - 15^th International Conference on Computer-Supported Collaborative Learning, Hiroshima, Japan, pp. 324-327 (2022)
  • R. Azevedo, F. Bouchet, M. Duffy, J. Harley, M. Taub, G. Trevors, E. Cloude, D. Dever, M. Wiedbusch, F. Wortha, R. Cerezo : “Lessons Learned and Future Directions of MetaTutor: Leveraging Multichannel Data to Scaffold Self-Regulated Learning With an Intelligent Tutoring System”, Frontiers in Psychology, vol. 13, pp. 813632, (Frontiers Media) (2022)
  • Kh. Sylla, G. Mbatchou, F. Bouchet : “How does the Use of Open Digital Spaces Impact Students Success and Dropout in a Virtual University?”, 19^th International Conference on Cognition and Exploratory Learning in the Digital Age - CELDA 2022, Proceedings of the 19^th International Conference on Cognition and Exploratory Learning in the Digital Age, Lisbonne, Portugal, pp. 251-258, (ISBN: 978-989-8704-43-6) (2022)
• 2021
  • K. Oliver‑Quelennec, F. Bouchet, Th. Carron, C. Pinçon : “Can a Learning Analytics Dashboard Participative Design Approach Be Transposed to an Online-Only Context?”, 18^th International Conference Cognition and Exploratory Learning in Digital Age, Virtual, Portugal (2021)
  • Th. Sergent, F. Bouchet, M. Daniel, Th. Carron : “Using Prompts and Remediation to Improve Primary School Students Self-Evaluation and Self-Efficacy in a Literacy Web Application”, Technology-Enhanced Learning for a Free, Safe, and Sustainable World, vol. 12884, Lecture Notes in Computer Science, Bolzano, Italy, pp. 221-234, (Springer International Publishing) (2021)
  • Th. Sergent, M. Daniel, F. Bouchet, Th. Carron : “Addressing Children’s Self-Evaluation and Self-Efficacy Deficits in a Literacy Application”, 2021 International Conference on Advanced Learning Technologies (ICALT), IEEE 21^st International Conference on Advanced Learning Technologies, Tartu (online), Estonia, pp. 141-143, (IEEE) (2021)
  • I.‑H. Hsiao, Sh. Sahebi, F. Bouchet, J.‑J. Vie : “Proceedings of the 14^th International Conference on Educational Data Mining”, (ISBN: 978-1-7336736-2-4) (2021)
  • Th. Sergent, M. Daniel, F. Bouchet, Th. Carron : “Predicting Young Students’ Self-Evaluation Deficits Through Their Activity Traces”, 14^th International Conference on Educational Data Mining, Proceedings of the 14^th International Conference on Educational Data Mining, Paris, France, pp. 667-671 (2021)
  • F. Harrak, F. Bouchet : “Aide au suivi de la progression de groupes d’apprenants pour la mise en place d’une pédagogie différenciée”, 10^e Conférence sur les Environnements Informatiques pour l’Apprentissage Humain, Transformations dans le domaine des EIAH : innovations technologiques et d’usage(s), Fribourg, Switzerland, pp. 312-317 (2021)
  • Th. Sergent, M. Daniel, F. Bouchet, Th. Carron : “Analyse de remédiations proposées par des enseignants ciblant des déficits d’auto-régulation de jeunes élèves dans une application d’apprentissage de la lecture”, 10^e Conférence sur les Environnements Informatiques pour l’Apprentissage Humain, Transformations dans le domaine des EIAH : innovations technologiques et d’usage(s), Fribourg / Virtual, Switzerland, pp. 262-273 (2021)
  • Th. Sergent, F. Bouchet, M. Daniel, Th. Carron : “Détection de déficits d’auto-évaluation et d’auto-efficacité dans un logiciel enseignant la lecture et l’écriture”, 10^e Conférence sur les Environnements Informatiques pour l’Apprentissage Humain, Transformations dans le domaine des EIAH : innovations technologiques et d’usage(s), Fribourg / Virtual, Switzerland, pp. 250-261 (2021)
  • K. Oliver‑Quelennec, F. Bouchet, Th. Carron, C. Pinçon : “Faciliter le recueil de traces par la numérisation d’un outil tangible de co-design : application à la conception de tableaux de bord d’apprentissage”, 10^e Conférence sur les Environnements Informatiques pour l’Apprentissage Humain, Transformations dans le domaine des EIAH : innovations technologiques et d’usage(s), Fribourg, Switzerland, pp. 360-365 (2021)
  • C. Morais Canellas, F. Bouchet, V. Luengo : “Représentations sociales de l’analytique des apprentissages avec le numérique”, 10^e Conférence sur les Environnements Informatiques pour l’Apprentissage Humain, Transformations dans le domaine des EIAH : innovations technologiques et d’usage(s), Fribourg, Switzerland, pp. 354-359 (2021)
  • C. Canellas, F. Bouchet, Th. Arribe, V. Luengo : “Towards Learning Analytics Metamodels in a Context of Publishing”, Proceedings of the 13^th International Conference on Computer Supported Education, vol. 2, Prague (virtual), Czechia, pp. 45-54, (SciTePress) (2021)
  • M. Barzman, M. Gerphagnon, G. Aubin‑Houzelstein, G.‑L. Baron, A. Benard, F. Bouchet, J. Dibie‑Barthelemy, J.‑F. Gibrat, S. Hodson, E. Lhoste, C. Martin, Y. Moulier‑Boutang, S. Perrot, F. Phung, Ch. Pichot, M. Siné, Th. Venin, O. Mora : “Exploring Digital Transformation in Higher Education and Research via Scenarios”, Journal of Futures Studies, vol. 25 (3), pp. 65-78, (Tamkang University) (2021)
  • F. Bouchet, D. Roy : “L’apport combiné de deux algorithmes d’IA à l’optimisation des parcours d’apprentissage dans le projet Adaptiv’Math”, 47^e colloque de la COPIRELEM, Dispositifs et collectifs pour la formation, l’enseignement et l’apprentissage des mathématiques, Grenoble, France, pp. 855-868, (ARPEME) (2021)
  • K. Oliver‑Quelennec, F. Bouchet, Th. Carron, C. Pinçon : “Analyzing the Impact of e-Caducée, a Serious Game in Pharmacy on Students’ Professional Skills over Multiple Years”, CSEDU 2021 - 13^th International Conference on Computer Supported Education, vol. 1, Proceedings of the 13^th International Conference on Computer Supported Education, Prague (virtual), Czechia, pp. 331-338, (SciTePress - Science and Technology Publications) (2021)
• 2020
  • G. Mbatchou Nkwetchoua, F. Bouchet, Th. Carron, Ph. Pernelle : “Towards a Model of Learner-Directed Learning: An Approach Based on the Co-construction of the Learning Scenario by the Learner”, chapter in Online Teaching and Learning in Higher Education, Cognition and Exploratory Learning in the Digital Age, pp. 41-63, (Springer), (ISBN: 978-3-030-48190-2) (2020)
  • E. Poitras, R. Behnagh, F. Bouchet : “A Dimensionality Reduction Method for Time Series Analysis of Student Behavior to Predict Dropout in Massive Open Online Courses”, chapter in Adoption of Data Analytics in Higher Education Learning and Teaching, pp. 391-406, (ISBN: 978-3-030-47392-1) (2020)
  • Th. Sergent, F. Bouchet, Th. Carron : “Towards Temporality-Sensitive Recurrent Neural Networks through Enriched Traces”, International Conference on Educational Data Mining (EDM 2020), Ifrane, Morocco, pp. 658-661 (2020)
  • F. Harrak, F. Bouchet, V. Luengo, P. Gillois : “Evaluating Teachers’ Perceptions of Students’ Questions Organization”, Learning Analytics & Knowledge Conference, LAK '20: Proceedings of the Tenth International Conference on Learning Analytics & Knowledge, Frankfurt, Germany, pp. 11-16, (ACM) (2020)
  • Y. Noel, F. Bouchet, R. Mergoil, V. Luengo : “Towards a modular and flexible Learning Analytics framework”, Companion Proceedings of the 10^th International Conference on Learning Analytics & Knowledge LAK20, Frankfurt, Germany, pp. 178-179 (2020)
  • M. Barzman, M. Gerphagnon, O. Mora, G. Aubin‑Houzelstein, A. Benard, C. Martin, G.‑L. Baron, F. Bouchet, J. Dibie‑Barthelemy, J.‑F. Gibrat, S. Hodson, E. Lhoste, Y. Moulier‑Boutang, S. Perrot, F. Phung, Ch. Pichot, M. Siné, Th. Venin : “La transition numérique dans la recherche et l’enseignement supérieur à l’horizon 2040”, (éditions Quae), (ISBN: 9782759231522) (2020)
  • F. Harrak, F. Bouchet, V. Luengo : “Liens entre performance, assiduité et questions posées et votées en ligne dans le cadre d’une classe inversée”, STICEF (Sciences et Technologies de l'Information et de la Communication pour l'Éducation et la Formation), vol. 27 (2), (ATIEF) (2020)
• 2019
  • M. Vermeulen, A. Karami, A. Fleury, F. Bouchet, N. Mandran, J. Laval, J.‑M. Labat : “APACHES: Human-Centered and Project-Based Methods in Higher Education”, 14^th European Conference on Technology Enhanced Learning EC-TEL 2019, vol. 11722, Lecture Notes in Computer Science, Delft, Netherlands, pp. 683-687, (Springer) (2019)
  • F. Harrak, F. Bouchet, V. Luengo, R. Bachelet : “Automatic Identification of Questions in MOOC Forums and Association with Self-Regulated Learning”, Proc. of the 12^th International Conference on Educational Data Mining, Montréal, Canada, pp. 564-567 (2019)
  • F. Harrak, F. Bouchet, V. Luengo : “Categorizing students’ questions using an ensemble hybrid approach”, Proc. of the 12^th International Conference on Educational Data Mining, Montréal, Canada (2019)
  • F. Harrak, V. Luengo, F. Bouchet, R. Bachelet : “Towards Improving Students’ Forum Posts Categorization in MOOCs and Impact on Performance Prediction”, Proceedings of the Sixth (2019) ACM Conference on Learning @ Scale, Chicago, United States, pp. 47:1-47:4, (ACM Press) (2019)
  • F. Harrak, F. Bouchet, V. Luengo : “Comparaison de questions posées et votées en ligne dans le cadre d’une classe inversée”, Actes de la 9^e Conférence sur les Environnements Informatiques pour l'Apprentissage Humain, Paris, France, pp. 121-132 (2019)
  • F. Bouchet, R. Bachelet : “Socializing on MOOCs: comparing university and self-enrolled students”, Digital Education: At the MOOC Crossroads Where the Interests of Academia and Business Converge, vol. 11475, Lecture Notes in Computer Science, Naples, Italy, pp. 31-36, (Springer Nature) (2019)
  • F. Harrak, F. Bouchet, V. Luengo : “From Student Questions to Student Profiles in a Blended Learning Environment”, Journal of Learning Analytics, vol. 6 (1), pp. 54-84 (2019)
  • D. Camacho Vega, F. Bouchet : “Self-Regulated Learning: Comparing Online and Classroom Courses in Cognition, Metacognition, Motivation, Emotions, Contexts, and Behavior”, The 2019 Annual meeting of the American Educational Research Association, Toronto, Canada (2019)
  • M. Barzman, M. Gerphagnon, O. Mora, G. Aubin‑Houzelstein, A. Benard, C. Martin, G.‑L. Baron, F. Bouchet, J. Dibie‑Barthelemy, J.‑F. Gibrat, S. Hodson, E. Lhoste, Y. Moulier Boutang, S. Perrot, F. Phung, Ch. Pichot, M. Siné, Th. Venin : “Transition numérique et pratiques de recherche et d’enseignement supérieur en agronomie, environnement, alimentation et sciences vétérinaires à l’horizon 2040.: Rapport de la prospective”, 161 p. pages (2019)
• 2018
  • G. Mbatchou, F. Bouchet, Th. Carron, Ph. Pernelle : “Proposing and evaluating a model of co-construction of the learning scenario by the learner”, International Conference Cognition and Exploratory Learning in Digital Age, vol. ISBN: 978-989-8533-81-4, Proceedings of the 15^th International Conference Cognition and Exploratory Learning in Digital Age, Budapest, Hungary, pp. 208-215 (2018)
  • G. Mbatchou, F. Bouchet, Th. Carron : “Multi-scenario modelling of learning”, Actes de la 8^e Conférence sur le Recherche en Informatique et ses Applications, vol. 249, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Ziguinchor, Senegal, pp. 199-211, (Springer) (2018)
  • H. Labarthe, V. Luengo, F. Bouchet : “Analyse de l’hybridation entre les communautés LAK, EDM et AIED”, PFIA 2018 : Journée IA pour l'éducation, Nancy, France (2018)
  • H. Labarthe, V. Luengo, F. Bouchet : “Analyzing the relationships between learning analytics, educational data mining and AI for education”, ITS 2018 Workshop Proceedings 14^th International Conference, ITS 2018, Montreal, Canada, pp. 10-19 (2018)
  • F. Bouchet, J. Harley, R. Azevedo : “Evaluating Adaptive Pedagogical Agents’ Prompting Strategies Effect on Students’ Emotions”, Intelligent Tutoring Systems 14^th International Conference, ITS 2018, Montreal, QC, Canada, June 11–15, 2018, Proceedings, vol. 10858, Lecture Notes in Computer Science, Montreal, Canada, pp. 33-43 (2018)
  • J. Harley, F. Bouchet, R. Azevedo : “Examining How Students’ Typical Studying Emotions Relate to Those Experienced While Studying with an ITS”, ITS 2018 - 14^th International Conference on Intelligent Tutoring Systems, vol. 10858, Lecture Notes in Computer Science, Montreal, Canada, pp. 434-437, (Springer) (2018)
  • F. Harrak, F. Bouchet, V. Luengo, P. Gillois : “Profiling Students from Their Questions in a Blended Learning Environment”, LAK '18 Proceedings of the 8^th International Conference on Learning Analytics and Knowledge, Sydney, Australia, pp. 102-110, (ACM) (2018)
  • F. Bouchet, R. Bachelet, H. Labarthe, K. Yacef : “Apports d’un outil de recommandation de pairs pour lutter contre l’attrition”, Colloque e-Formation 2018, Villeneuve d'Ascq, France, pp. 431-432 (2018)
  • J. Harley, M. Taub, R. Azevedo, F. Bouchet : “Let’s Set Up Some Subgoals: Understanding Human-Pedagogical Agent Collaborations and Their Implications for Learning and Prompt and Feedback Compliance”, IEEE Transactions on Learning Technologies, vol. 11 (1), pp. 54-66, (Institute of Electrical and Electronics Engineers) (2018)
• 2017
  • B. Monterrat, A. Yessad, F. Bouchet, E. Lavoué, V. Luengo : “MAGAM: A Multi-Aspect Generic Adaptation Model for Learning Environments”, Data Driven Approaches in Digital Education, vol. 10474, Lecture Notes in Computer Science, Tallinn, Estonia, pp. 139-152, (Springer International Publishing) (2017)
  • F. Bouchet, H. Labarthe, K. Yacef, R. Bachelet : “Comparing Peer Recommendation Strategies in a MOOC”, UMAP’17 Adjunct, Bratislava, Slovakia, pp. 129-134, (ACM Press) (2017)
  • F. Harrak, F. Bouchet, V. Luengo : “Identifying relationships between students’ questions type and their behavior”, 10^th International Conference on Educational Data Mining, Wuhan, China (2017)
  • B. Monterrat, A. Yessad, F. Bouchet, E. Lavoué, V. Luengo : “MAGAM : un modèle générique pour l’adaptation multi-aspects dans les EIAH”, Environnements Informatiques pour l'Apprentissage Humain, EIAH 2017, Strasbourg, France, pp. 29-40 (2017)
  • F. Bouchet, H. Labarthe, R. Bachelet, K. Yacef : “Who wants to chat on a MOOC? Lessons from a peer recommender system”, Digital Education: Out to the World and Back to the Campus, vol. 10254, Lecture Notes in Computer Science, Madrid, Spain, pp. 150-159, (Springer, Cham) (2017)
  • G. Sambe, F. Bouchet, J.‑M. Labat : “Towards a conceptual framework to scaffold self-regulation in a MOOC”, Sixième Colloque National sur la Recherche en Informatique et ses Applications, CNRIA 2017, vol. 204, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Dakar, Senegal, pp. 245-256, (Springer) (2017)
  • B. Monterrat, F. Bouchet, E. Lavoué, V. Luengo : “Vers une adaptation des apprentissages générique et multi-aspects”, ORPHEE-RDV 2017 Atelier "Personnalisation et adaptation dans les environnements d'apprentissage : un regard interdisciplinaire sur les perspectives de recherche" -, Font-Romeu, France, pp. 4p. (2017)
• 2016
  • H. Labarthe, F. Bouchet, R. Bachelet, K. Yacef : “Does a Peer Recommender Foster Students’ Engagement in MOOCs?”, Proceedings of the 9^th International Conference on Educational Data Mining, Raleigh, United States, pp. 418-423 (2016)
  • F. Bouchet, J. Harley, R. Azevedo : “Can Adaptive Pedagogical Agents’ Prompting Strategies Improve Students’ Learning and Self-Regulation?”, 13^th International Conference Intelligent Tutoring Systems:, Intelligent Tutoring Systems, Zagreb, Croatia, pp. 368-374 (2016)
  • N. Papaioannou, Ronald S. Landis, Cassia K. Carter, R. Azevedo, F. Bouchet, Jason M. Harley : “Computer-based Learning Environments in Organizational Training: Impact of Learning Environment and Personality”, 28^th Annual Convention of the Association for Psychological Science, Chicago, United States (2016)
  • J. Ranellucci, E. Poitras, F. Bouchet, S. Lajoie, N. Hall : “Understanding Emotional Expressions in Social Media through Data Mining”, chapter in Emotions, Technology, and Social Media, pp. 85-104, (Academic Press), (ISBN: 978-0-12-801857-6) (2016)
  • R. Feyzi‑Behnagh, R. Azevedo, F. Bouchet, Y. Tian : “The role of an open learner model and immediate feedback on metacognitive calibration in MetaTutor”, The 2016 Annual meeting of the American Educational Research Association, Washington, DC, United States (2016)
  • G. Trevors, R. Feyzi‑Behnagh, R. Azevedo, F. Bouchet : “Self-Regulated Learning Processes Vary as a Function of Epistemic Beliefs and Contexts: Mixed Method Evidence from Eye Tracking and Concurrent and Retrospective Reports”, Learning and Instruction, vol. 42, pp. 31-46, (Elsevier) (2016)
  • H. Labarthe, R. Bachelet, F. Bouchet, K. Yacef : “Increasing MOOC completion rates through social interactions: a recommendation system”, EMOOCS 2016 Conference. Fourth European MOOCS Stakeholders Summit, Graz, Austria, pp. 471-480 (2016)
  • Jason M. Harley, Cassia K. Carter, N. Papaioannou, F. Bouchet, Ronald S. Landis, R. Azevedo, L. Karabachian : “Examining the predictive relationship between personality and emotion traits and students’ agent-directed emotions: towards emotionally-adaptive agent-based learning environments”, User Modeling and User-Adapted Interaction, vol. 26 (2), pp. 177-219, (Springer Verlag) (2016)
• 2015
  • N. Mudrick, R. Azevedo, M. Taub, F. Bouchet : “Does the Frequency of Pedagogical Agent Intervention Relate to Learners’ Self-Reported Boredom while using Multi-Agent Intelligent Tutoring Systems?”, Proc. of the 37^th Annual Meeting of the Cognitive Science Society, Pasadena, CA, United States, pp. 1661-1666 (2015)
  • Jason M. Harley, F. Bouchet, M. Sazzad Hussain, R. Azevedo, Rafael A. Calvo : “A Multi-Componential Analysis of Emotions during Complex Learning with an Intelligent Multi-agent System”, Computers in Human Behavior, vol. 48, pp. 615-625, (Elsevier) (2015)
  • F. Bouchet, R. Bachelet : “Do MOOC students come back for more? Recurring Students in the GdP MOOC”, Proc. of the European MOOCs Stakeholders Summit 2015, Mons, Belgium, pp. 174-182 (2015)
  • Jason M. Harley, Cassia K. Carter, N. Papaioannou, F. Bouchet, Ronald S. Landis, R. Azevedo, L. Karabachian : “Examining the predictive relationship between personality and emotion traits and learners’ agent-directed emotions”, Proc. of the 17^th Conference on Artificial Intelligence in Education (AIED 2015), vol. 9112, Lecture Notes in Artificial Intelligence, Madrid, Spain, pp. 145-154, (Springer International Publishing) (2015)
• 2014
  • M. Taub, R. Azevedo, F. Bouchet, B. Khosravifar : “Can the use of cognitive and metacognitive self-regulated learning strategies be predicted by learners’ levels of prior knowledge in hypermedia-learning environments?”, Computers in Human Behavior, vol. 39, pp. 356-367, (Elsevier) (2014)
  • N. Mudrick, R. Azevedo, M. Taub, R. Feyzi‑Behnagh, F. Bouchet : “A Study of subjective emotions, self-regulatory processes, and learning gains: are pedagogical agents effective in fostering learning?”, Learning and becoming in practice : The International Conference of the Learning Sciences (ICLS) 2014, vol. 1, Boulder, CO, United States, pp. 309-316, (International Society of the Learning Sciences) (2014)
  • M. Taub, R. Azevedo, N. Mudrick, E. Clodfelter, F. Bouchet : “Can Scaffolds from Pedagogical Agents Influence Effective Completion of Sub-Goals during Learning with a Multi-Agent Hypermedia-Learning Environment?”, Learning and becoming in practice : The International Conference of the Learning Sciences (ICLS) 2014, vol. 2, Boulder, CO, United States, pp. 1052-1056, (International Society of the Learning Sciences) (2014)
  • M. Duffy, R. Azevedo, S. Meterissian, F. Bouchet : “VirtualSelf: A computer-based learning environment for patient education using physiological and trace data”, IIE Annual 2014, Montreal, QC, Canada (2014)
  • Jason M. Harley, F. Bouchet, M. Sazzad Hussain, R. Azevedo, Rafael A. Calvo : “A Multi-Componential Analysis of Emotions during Complex Learning with an Intelligent Multi-Agent System”, The 2014 Annual meeting of the American Educational Research Association, Philadelphia, PA, United States (2014)
  • J. Ranellucci, F. Bouchet, Eric G. Poitras, Susanne P. Lajoie, R. Azevedo : “An analysis of emotions in educationally relevant tweets”, The 2014 Annual meeting of the American Educational Research Association, Philadelphia, PA, United States (2014)
  • Jason M. Harley, F. Bouchet, N. Papaioannou, C. Carter, Gregory J. Trevors, R. Feyzi‑Behnagh, R. Azevedo, Ronald S. Landis : “Assessing Learning with MetaTutor, a Multi-Agent Hypermedia Learning Environment”, The 2014 Annual meeting of the American Educational Research Association, Philadelphia, PA, United States (2014)
  • J.‑P. Sansonnet, F. Bouchet : “A Framework Covering the Influence of FFM/NEO PI-R Traits over the Dialogical Process of Rational Agents”, 5^th International Conference on Agents and Artificial Intelligence, ICAART 2013, vol. 449, Communications in Computer and Information Science, Barcelona, Spain, pp. 62-79, (Springer) (2014)
  • Jason M. Harley, F. Bouchet, M. Sazzad Hussain, R. Azevedo, Rafael A. Calvo : “A Multi-Componential Analysis of Emotions during Complex Learning with an Intelligent Multi-Agent System”, The 2014 Annual meeting of the American Educational Research Association, Philadelphia, PA, USA (2014)
  • N. Mudrick, R. Azevedo, M. Taub, R. Feyzi‑Behnagh, F. Bouchet : “A Study of subjective emotions, self-regulatory processes, and learning gains: are pedagogical agents effective in fostering learning?”, Learning and becoming in practice : The International Conference of the Learning Sciences (ICLS) 2014, vol. 1, Joseph L. Polman, Eleni A. Kyza, D. Kevin O'Neill, I. Tabak, William R. Penuel, A. Susan Jurow, K. O'Connor, T. Lee, L. D'Amico (Eds.), Boulder, CO, USA, pp. 309-316, (International Society of the Learning Sciences), (ISBN: 1814-9316) (2014)
  • J. Ranellucci, F. Bouchet, Eric G. Poitras, Susanne P. Lajoie, R. Azevedo : “An analysis of emotions in educationally relevant tweets”, The 2014 Annual meeting of the American Educational Research Association, Philadelphia, PA, USA (2014)
  • Jason M. Harley, F. Bouchet, N. Papaioannou, C. Carter, Gregory J. Trevors, R. Feyzi‑Behnagh, R. Azevedo, Ronald S. Landis : “Assessing Learning with MetaTutor, a Multi-Agent Hypermedia Learning Environment”, The 2014 Annual meeting of the American Educational Research Association, Philadelphia, PA, USA (2014)
  • M. Taub, R. Azevedo, N. Mudrick, E. Clodfelter, F. Bouchet : “Can Scaffolds from Pedagogical Agents Influence Effective Completion of Sub-Goals during Learning with a Multi-Agent Hypermedia-Learning Environment?”, Learning and becoming in practice : The International Conference of the Learning Sciences (ICLS) 2014, vol. 2, Joseph L. Polman, Eleni A. Kyza, D. Kevin O'Neill, I. Tabak, William R. Penuel, A. Susan Jurow, K. O'Connor, T. Lee, L. D'Amico (Eds.), Boulder, CO, USA, pp. 1052-1056, (International Society of the Learning Sciences), (ISBN: 1814-9316) (2014)
  • M. Duffy, R. Azevedo, S. Meterissian, F. Bouchet : “VirtualSelf: A computer-based learning environment for patient education using physiological and trace data”, IIE Annual 2014, Montreal, QC, Canada, (ISBN: 978-0-98337624-3-0) (2014)
• 2013
  • F. Bouchet, J.‑P. Sansonnet : “Agents Conversationnels Psychologiques : Modélisation des réactions rationnelles et comportementales des agents assistants conversationnels”, Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, vol. 27 (6), pp. 679-708, (Lavoisier) (2013)
  • F. Bouchet, Jason M. Harley, Gregory J. Trevors, R. Azevedo : “Clustering and Profiling Students According to their Interactions with an Intelligent Tutoring System Fostering Self-Regulated Learning”, Journal of Educational Data Mining, vol. 5 (1), pp. 104-146, (ISBN: 2157-2100) (2013)
  • F. Bouchet, J.‑P. Sansonnet : “Influence of FFM/NEO PI-R personality traits on the rational process of autonomous agents”, Web Intelligence and Agent Systems, vol. 11 (3), pp. 203-220, (ISBN: 1570-1263) (2013)
  • J.‑P. Sansonnet, F. Bouchet : “A Framework Covering the Influence of FFM/NEO PI-R Traits over the Dialogical Process of Rational Agents”, 5^th International Conference on Agents and Artificial Intelligence, ICAART 2013, vol. 449, Communications in Computer and Information Science, J. Filipe, A. Fred (Eds.), Barcelona, Spain, pp. 62-79, (Springer Berlin Heidelberg), (ISBN: 978-3-662-44439-9) (2013)
  • Jason M. Harley, F. Bouchet, R. Azevedo : “Aligning and Comparing Data on Emotions Experienced during Learning with MetaTutor”, Proc. of the 16^th Conference on Artificial Intelligence in Education (AIED 2013), vol. 7926, Lecture Notes in Computer Science, H. Chad Lane, K. Yacef, J. Mostow, Ph. Pavlik (Eds.), Memphis, TN, pp. 61-70, (Springer Berlin Heidelberg), (ISBN: 978-3-642-39111-8) (2013)
  • F. Bouchet, Jason M. Harley, R. Azevedo : “Impact of Different Pedagogical Agents’ Adaptive Self-Regulated Prompting Strategies on Learning with MetaTutor”, Proc. of the 16^th Conference on Artificial Intelligence in Education (AIED 2013), vol. 7926, Lecture Notes in Computer Science, H. Chad Lane, K. Yacef, J. Mostow, Ph. Pavlik (Eds.), Memphis, TN, pp. 815-819, (Springer Berlin Heidelberg), (ISBN: 978-3-642-39111-8) (2013)
  • D. Bondareva, C. Conati, R. Feyzi‑Behnagh, Jason M. Harley, R. Azevedo, F. Bouchet : “Inferring Learning from Gaze Data during Interaction with an Environment to Support Self-Regulated Learning”, Proc. of the 16^th Conference on Artificial Intelligence in Education (AIED 2013), vol. 7926, Lecture Notes in Computer Science, H. Chad Lane, K. Yacef, J. Mostow, Ph. Pavlik (Eds.), Memphis, TN, pp. 229-238, (Springer Berlin Heidelberg), (ISBN: 978-3-642-39111-8) (2013)
  • J.‑P. Sansonnet, F. Bouchet : “Managing personality influences in dialogical agents”, 5^th International Conference on Agents and Artificial Intelligence, ICAART 2013, J. Filipe, A. Fred (Eds.), Barcelona, Spain, pp. 89-98 (2013)
• 2012
  • F. Bouchet, J.‑P. Sansonnet : “Traits de Personnalité Computationnels: Enrichissement de la taxonomie FFM/NEO PI-R avec des gloses WordNet liées à des adjectifs de personnalité”, Technique et Science Informatiques, vol. 31 (4), pp. 423-453, (ISBN: 0752-4072) (2012)
  • F. Bouchet, John S. Kinnebrew, G. Biswas, R. Azevedo : “Identifying Students’ Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning”, Proceedings of the 5^th International Conference on Educational Data Mining, K. Yacef, O. Zaïane, A. Hershkovitz, M. Yudelson, J. Stamper (Eds.), Chania, Greece, pp. 65-72, (ISBN: 978-1-74210-276-4) (2012)
  • Jason M. Harley, F. Bouchet, R. Azevedo : “Measuring Learners’ Co-Occurring Emotional Responses during their Interaction with a Pedagogical Agent in MetaTutor”, Intelligent Tutoring Systems, 11^th International Conference, vol. 7315, Lecture Notes in Computer Science, Stefano A. Cerri, William J. Clancey, G. Papadourakis, K. Panourgia (Eds.), Chania, Greece, pp. 40-45, (Springer), (ISBN: 978-3-642-30949-6) (2012)
  • R. Azevedo, Ronald S. Landis, R. Feyzi‑Behnagh, M. Duffy, Gregory J. Trevors, Jason M. Harley, F. Bouchet, J. Burlison, M. Taub, N. Pacampara, M. Yeasin, A. K. Mahbubur M. Rahman, M. Iftekhar Tanveer, G. Hossain : “The Effectiveness of Pedagogical Agents’ Prompting and Feedback in Facilitating Co-Adapted Learning with MetaTutor”, Intelligent Tutoring Systems, 11^th International Conference, vol. 7315, Lecture Notes in Computer Science, Stefano A. Cerri, William J. Clancey, G. Papadourakis, K. Panourgia (Eds.), Chania, Greece, pp. 212-221, (Springer), (ISBN: 978-3-642-30949-6) (2012)
• 2011
  • F. Bouchet, J.‑P. Sansonnet : “Agents Conversationnels Psychologiques : Un cadre d’étude des comportements rationnels et psychologiques des agents assistants conversationnels”, Revue des Sciences et Technologies de l'Information - Série RIA : Revue d'Intelligence Artificielle, vol. 25 (5), pp. 591-623, (ISBN: 0992-499X) (2011)
  • F. Bouchet, J.‑P. Sansonnet : “Implementing WordNet Personality Adjectives as Influences on Rational Agents”, International Journal of Computer Information Systems and Industrial Management Applications, vol. 3 (1), pp. 696-705, (ISBN: 2150-7988) (2011)
  • E. Miletto, M. Pimenta, F. Bouchet, J.‑P. Sansonnet, D. Keller : “Principles for Music Creation by Novices in Networked Music Environments”, Journal of New Music Research, vol. 40 (3), pp. 205-216, (ISBN: 0929-8215) (2011)
• 2010
  • M. Xuetao, J.‑P. Sansonnet, F. Bouchet : “Définition d’un agent conversationnel assistant d’applications Internet à partir d’un corpus de requêtes”, Technique et Science Informatiques, vol. 29 (10), pp. 1123-1154, (ISBN: 0752-4072) (2010)