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Your search keyword '"Susan Zvacek"' showing total 2 results
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2 results on '"Susan Zvacek"'

1. Lecture notes Learner Models for MOOC in a Lifelong LearningContext: A Systematic Literature Review

Author

Ramirez, Sergio, El Mawas, Nour, Heutte, Jean, Trigone-CIREL, Centre Interuniversitaire de Recherche en Education de Lille - ULR 4354 (CIREL), Université de Lille-Université de Lille, Université Lille 1 - Département Sciences de l'éducation et de la formation (CUEEP SEFA), Université de Lille, Sciences et Technologies, Université de Lille, H. C. Lane, Susan Zvacek, James Uhomoibhi, and ANR-16-IDEX-0004,ULNE,ULNE(2016)

Subjects
Learning Environment, Lifelong Learning, literature review, [SHS.EDU]Humanities and Social Sciences/Education, knowledge representation, Learner Model, [INFO.EIAH]Computer Science [cs]/Technology for Human Learning, Technology Enhanced Learning, Learning Analytics, MOOC
Abstract

International audience; While setting up a Massive Open Online Course for Lifelong Learners, the choice of the most adequate Learner Model for this most current contextis paramount: not all Learner Models are created equal, despite their overalladded value to facilitate the learner’s follow-up, course content personalizationand trainers/teachers’ practices in various Learning Environments. This systematic review of literature defines, compares, and highlights eight features of interest of Learner Models for Massive Open Online Courses from a LifelongLearning perspective. It discerns 17 of the most-current, existing Learner Models out of 442 search results. It concludes on the four most adequate, and current Learner Models in this context. In addition, we study how they handle thelearning experience personalization. This work is primarily dedicated to MOOCdesigners/providers, pedagogical engineers and researchers who meet difficulties to model and evaluate MOOC’s learners using Learning Analytics.

Published
2021
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2. An Authoring Tool to Elicit Knowledge to be Taught without Programming

Author

Vanda Luengo, Nathalie Guin, Amélie Cordier, Awa Diattara, Traces, Web, Education, Adaptation, Knowledge (TWEAK), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Université Lumière - Lyon 2 (UL2), Modèles et Outils en ingénierie des Connaissances pour l'Apprentissage Humain (MOCAH), Laboratoire d'Informatique de Paris 6 (LIP6), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Systèmes Cognitifs et Systèmes Multi-Agents (SyCoSMA), Paula Escudeiro, Gennaro Costagliola, Susan Zvacek, James Uhomoibhi, Bruce M. McLaren, Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), and Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Problem Solving Methods, Multimedia, Computer science, Process (engineering), 4. Education, Context (language use), Intelligent Tutoring Systems, computer.software_genre, Knowledge acquisition, Variety (cybernetics), Domain (software engineering), Human–computer interaction, [INFO.EIAH]Computer Science [cs]/Technology for Human Learning, Knowledge Acquisition, computer, Authoring Tool
Abstract

International audience; Knowledge acquisition is a crucial problem for the design of Intelligent Tutoring Systems (ITSs). To overcome this problem, authoring tools have been proposed. Over two dozen of authoring tools have been built since the earliest days of ITS, but each of them focuses on a particular kind of ITSs such as constraint-based tutors or model-tracing tutors. In the context of the AMBRE project, we are interested in ITSs teaching problem-solving methods. Such ITSs enable learners to acquire a specific method in problem-solving. Despite of the variety of existing authoring tools, these tools do not meet our needs either because approach adopted do not match to AMBRE principle or because they do not allow to represent all knowledge needed to design an AMBRE ITS. We propose AMBRE-KB, an authoring tool to help authors to elicit knowledge needed for the design of AMBRE ITSs. This tool supports the acquisition of knowledge to be taught, and the description of problems to be solved. We present the authoring process and illustrate it using French verb conjugation domain. A preliminary evaluation shows that AMBRE-KB is successful in producing domains models but more thorough evaluation is planned.

Published
2017
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