Sergio Iván Ramírez Luelmo
Compétences
Publications
Publications
Detection and Asynchronous Flow Prediction in a MOOCSN Computer Science, 2024, 5, pp.[En ligne]. ⟨10.1007/s42979-024-02838-w⟩ |
Searching concordance between two measurement tools (EduFlow-2 and FlowQ): Proposal for Flow State Method Detection in Educational and Training Contexts11th European Conference on Positive Psychology (ECPP 2024), University Innsbruck, Jul 2024, Innsbruck, Austria |
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Loss of Self-Consciousness and autotelic personalities: a Machine Learning contribution11th European Conference on Positive Psychology (ECPP 2024), University of Innsbruck, Jul 2024, Innsbruck, Austria |
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Detecting Flow via a Machine Learning Model in a MOOC Context5th International conference on Deep learning theory and applications, ESEO, Jul 2024, Dijon, France. pp.123-142, ⟨10.1007/978-3-031-66694-0_8⟩ |
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Towards a Machine Learning flow-predicting model in a MOOC context14th International Conference on Computer Supported Education (CSEDU 2022), Apr 2022, Online Streaming, United Kingdom |
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Lexicometrical analysis method to support Scoping Review on social dimensions of flow10th European Conference on Positive Psychology (ECPP 2022), Jun 2022, Reykjavik, Iceland |
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Advances on a Machine Learning flow prediction model in a MOOC11th European Flow Researchers Network, (EFRN) meeting, Nov 2022, Lille (Université de Lille), France |
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Prédire l’Expérience Autotélique des participants à un MOOC : Vers une implémentation du modèle EduFlow dans un Tableau de Bord9e Colloque international en éducation, Centre de recherche interuniversitaire sur la formation et la profession enseignante (CRIFPE), May 2022, Montréal, Canada |
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Machine Learning for Knowledge Tracing in Learner Models8e Colloque international en éducation, Centre de recherche interuniversitaire sur la formation et la profession enseignante (CRIFPE), Apr 2021, Montéal, Canada |
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Machine Learning techniques for Knowledge Tracing: A systematic literature reviewProceedings of the 13th International Conference on Computer Supported Education (CSEDU), 2021, Prague, Czech Republic. ⟨10.5220/0010515500600070⟩ |
Towards open learner models including the flow state.UMAP 20 Adjunct, ACM Conference on User Modeling, Adaptation and Personalization, 2020, Genoa, Italy. ⟨10.1145/3386392.3399295⟩ |
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Learner Models in MOOCs in a Lifelong Learning perspective7e Colloque international en éducation, CRIFPE, Apr 2020, Montréal, Canada |
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Institutionalization of Academic Research on the Social Dimensions of Flow8th European Flow-Researchers’ Network Meeting, Aarhus University, Department of Education (DPU), Nov 2019, Aarhus, Denmark |
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Des espaces-temps à l’épreuve du numériqueNumérique et lien social : appréhensions de la subjectivité et de l'altérité, Oct 2019, Angers, France |
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Le numérique éducatif à l'école élémentaire en tension entre politiques nationales, politiques locales et logiques d'appropriation par les enseignantsEcoles, territoires et numérique : quelles collaborations ? quels apprentissages ?, Oct 2019, Clermont-Ferrand, France |
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Analyse des parcours des apprenants du MOOC « La classe inversée à l’ère du numérique ».Colloque International Éducation 4.1 !, Jan 2019, Poitiers, France |
Observer les traces d’interaction pour comprendre les usages numériquesAtelier « Méthodologies et outils pour le recueil, l’analyse et la visualisation de traces numériques d’interaction » des ORPHEE Rendez-Vous, Jan 2017, Font-Romeu, France |
Optimal experience modelling: detection via Learning Analytics in a Lifelong Learning context10th European Conference on Positive Psychology (ECPP 2022), Jun 2022, Reykjavik, Iceland |
Machine Learning techniques for Knowledge Tracing: A systematic literature reviewin J. Uhomoibhi. Proceedings of the 13th International Conference on Computer Supported Education (CSEDU), Science and Technology Publications, Lda, In press |
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Lecture notes Learner Models for MOOC in a Lifelong Learning Context: A Systematic Literature ReviewH. C. Lane; Susan Zvacek; James Uhomoibhi. Lecture notes in Communications in Computer and Information Science (CCIS), Springer, pp.392-415, 2021, ⟨10.1007/978-3-030-86439-2_20⟩ |
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A literature review on Learner Models for MOOC to support Lifelong LearningH. C. Lane; S. Zvacek; J. Uhomoibhi. Proceedings of the 12th International Conference on Computer Supported Education (CSEDU), 1, Science and Technology Publications, Lda, pp.527-539, 2020, 978-989-758-417-6 |
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A literature review on Learner Models for MOOC to support Lifelong Learningin H. C. Lane, S. Zvacek and J. Uhomoibhi. Proceedings of the 12th International Conference on Computer Supported Education (CSEDU), 1, Science and Technology Publications, Lda, pp.527-539, 2020, 978-989-758-417-6 |
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Towards Open Learner Models including the Flow stateIn T. Kuflik & I. Torre (dir.). UMAP '20 Adjunct: Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization, Association for Computing Machinery, New York, NY United States, pp.305-310, 2020, 978-1-4503-7950-2. ⟨10.1145/3386392.3399295⟩ |
Le numérique à l’école élémentaire en France : ses usages et son financement par les collectivités territoriales[Rapport de recherche] Cour des comptes. 2019 |
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Accompagnement scientifique du projet Living Cloud du LP2I - Rapport final[Rapport de recherche] Université de Poitiers, Techne. 2017 |
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Rapport final sur l’accompagnement scientifique du projet Living Cloud au LP2I[Rapport de recherche] Université de Poitiers. 2017 |
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Automatic flow (optimal learning experience) detection in a MOOC via Machine Learning : Flow & Learning AnalyticsEducation. Université de Lille, 2023. English. ⟨NNT : 2023ULILH026⟩ |