Jacqueline Bourdeau

LICEF Research Center, Montréal, Quebec, Canada

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Publications (56)2.95 Total impact

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    Yusuke Hayashi · Seiji Isotani · Jacqueline Bourdeau · Riichiro Mizoguchi
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    Yusuke HAYASHI · Jacqueline BOURDEAU · Riichiro MIZOGUCHI
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    ABSTRACT: On the basis of the achievements of OMNIBUS project, this paper presents the functionality of theory-aware authoring system and discusses how to accumulate learn- ing/instructional design knowledge as the foundations for theory-awareness. The concept of "WAY" proposed by this study would be helpful for both utilizing and abstracting learning/ instructional design knowledge. Structuralization of WAY in an IS-A hierarchy is the key point toward accumulation of learning/instructional design knowledge.
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    Yusuke Hayashi · Jacqueline Bourdeau · Riichiro Mizoguchi
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    ABSTRACT: One of the problems to build theory-based authoring systems is the difficulty in building and sustainable maintenance of the knowledge base. This paper discusses an ontological structure for the accumulation of learn-ing/instructional design knowledge. Based on the past results of the OMNIBUS project, we present layering of the scenario model to introduce fundamental conceptualization of WAY knowledge followed by a discussion on how to ab-stract WAY knowledge from theoretical literature and/or scenarios found in best practices using an example of structuralization of theoretical knowledge.
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    Yusuke Hayashi · Seiji Isotani · Jacqueline Bourdeau · Riichiro Mizoguchi
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    ABSTRACT: This paper proposes an ontological model that is a flexible framework to create learning scenarios blending didactic and collaborative learning. This model enables us to describe the design rationale of such learning scenarios and to organize theoretical knowledge for designing such scenarios in the same manner.
    06/2011: pages 459-461;
  • Danièle Allard · Jacqueline Bourdeau · Riichiro Mizoguchi
    05/2011; 28(3):677-698. DOI:10.11139/cj.28.3.677-698
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    Yusuke Hayashi · Seiji Isotani · Jacqueline Bourdeau · Riichiro Mizoguchi
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    ABSTRACT: Didactic learning that follows the "traditional" model of a teacher-student relationship is often considered completely different from collaborative learning. As a result, few studies have explored the potential to effectively connect these two forms of learning. Nevertheless, in practice, a well-though-tout linkage between these different approaches is essential to leverage and facilitate the learning process. Thus, in this paper, we propose an ontological model that captures the similarity between the two forms of learning, with a focus on participants' interactions. One of the benefits of this model is the creation of a flexible framework to describe learning independently of the approach used to learn. Second, it also enables us to describe the design rationale of learning scenarios and to organize theoretical knowledge for designing such scenarios in the same manner. To validate this model, we show its advantages with the examination in modeling theories for didactic and collaborative learning, and describe the development of an authoring tool for learning design that uses the model to facilitate the design of theory-based blended learning scenarios.
    Lecture Notes in Computer Science 01/2011; 6969:1-13. DOI:10.1007/978-3-642-23801-7_1 · 0.51 Impact Factor
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    Yusuke Hayashi · Seiji Isotani · Jacqueline Bourdeau · Riichiro Mizoguchi
    Artificial Intelligence in Education - 15th International Conference, AIED 2011, Auckland, New Zealand, June 28 - July 2011; 01/2011
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    ABSTRACT: Computer-supported Collaborative Learning (CSCL) is an interdisciplinary research field that gathers researchers from different backgrounds around one common goal: to facilitate the design, deployment, and analysis of collaborative learning activities whose participants (primarily, students and instructors) are supported by information and communication technologies. CSCL researchers at tempt to understand how learning emerges in group settings, and how to create effective scenarios that enable learning through interaction, exploration, negotiation, discussion, and collaborative knowledge construction. Thus, CSCL has contributed to the development of the Learning Sciences by bringing into focus the need to understand the nature, theory, and practice of how we learn in collaborative settings supported by advanced technologies.
    IEEE Transactions on Learning Technologies 01/2011; 4(1):1-4. DOI:10.1109/TLT.2011.7 · 1.22 Impact Factor
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    Roger Nkambou · Jacqueline Bourdeau · Valéry Psyché
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    ABSTRACT: This chapter addresses the challenge of building or authoring an Intelligent Tutoring System (ITS), along with the problems that have arisen and been dealt with, and the solutions that have been tested. We begin by clarifying what building an ITS entails, and then position today’s systems in the overall historical context of ITS research. The chapter concludes with a series of open questions and an introduction to the other chapters in this part of the book.
    09/2010: pages 361-375;
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    Riichiro Mizoguchi · Yusuke Hayashi · Jacqueline Bourdeau
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    ABSTRACT: This chapter discusses an ontological approach to tutoring actions design as a special case of target-world modeling. Although a lot of research on the learner model has been done to improve the adaptivity of intelligent tutoring systems (ITSs), the modeling of tutoring actions has not been sufficiently investigated. The authors have been performing ontological modeling of learning/instructional theories to remedy this situation. Intelligent tutoring systems must have a good number of primitive actions to generate intelligent actions. Paying close attention to the importance of modeling tutoring actions, we have developed an ontology of learning/instructional theories, named OMNIBUS, in the ITS domain. Drawing on our long experience in ontological engineering research, this chapter discusses the modeling of tutoring actions as well as target-world modeling per se, using an example of learning/instructional actions from the OMNIBUS/SMARTIES project.
    09/2010: pages 229-247;
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    Jacqueline Bourdeau · Monique Grandbastien
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    ABSTRACT: This chapter introduces Part II on modeling tutoring knowledge in ITS research. Starting with its origin and with a characterization of tutoring, it proposes a general definition of tutoring, and a description of tutoring functions, variables, and interactions. The Interaction Hypothesis is presented and discussed, followed by the development of the tutorial component of ITSs, and their evaluation. New challenges are described, such as integrating the emotional states of the learner. Perspectives of opening the Tutoring Model and of equipping it with social intelligence are also presented.
    09/2010: pages 123-143;
  • Roger Nkambou · Riichiro Mizoguchi · Jacqueline Bourdeau
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    ABSTRACT: The idea for this book on Intelligent Tutoring Systems (ITS) was sparked by the success of the ITS’08 international conference. The number of presentations and their quality bore witness to the vitality and maturity of the field, and the enthusiasm of the participants held out a promise of sustainability and innovative research. Long life to ITS research! The book is divided into five parts. The introductory chapters to these parts, which summarize foundations, developments, strengths and weaknesses in each of the areas covered, are addressed to all readers. For those who want more in-depth knowledge, we give the floor to researchers who present their work, their results, and their view of what the future holds. It is our hope that all readers will find the book informative and thought-provoking. (http://www.springer.com/engineering/computational+intelligence+and+complexity/book/978-3-642-14362-5)
  • Yusuke Hayashi · Jacqueline Bourdeau · Riichiro Mizoguchi
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    ABSTRACT: Structuring learning/instructional theories suffer from the issue of 'paradigms', which makes them even more challenging. This paper discusses the conceptualisation of the theories and proposes a mechanism to provide perspectives for understanding and utilising them. Two types of conceptualisation proposed in this paper reveal their characteristics from a variety of viewpoints.
    01/2010; 1(3/4):187-208. DOI:10.1504/IJKWI.2010.034187
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    Yusuke Hayashi · Jacqueline Bourdeau · Riichiro Mizoguchi
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    ABSTRACT: This study, through the ontological engineering approach, aims at building a conceptual basis that encourages instructional designers in better understanding of learning/instructional theories, which mean that instructional designers can select and integrate appropriate strategies from theories within an instructional context. This paper proposes a methodology of structuring the theories in terms of strategies included in them, in which strategies can be structured independent of paradigms and theories.
    Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling, Proceedings of the 14th International Conference on Artificial Intelligence in Education, AIED 2009, July 6-10, 2009, Brighton, UK; 01/2009
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    ABSTRACT: Using as data videotapes of archaeologists working to see and map structure in the dirt they are excavating, meaning-making in the home of a man with severe aphasia, and sequences of actual talk-in-interaction, this talk will investigate action, cognition, ...
    Proceedings of the 8th International Conference on Computer Supported Collaborative Learning, CSCL'09, Rhodes, Greece, June 8-13, 2009, Volume 2; 01/2009
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    Yusuke Hayashi · Jacqueline Bourdeau
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    ABSTRACT: This paper describes the achievements of an innovative eight-year research program first introduced in Mizoguchi and Bourdeau (2000), which was aimed at building a theory-aware authoring system by using ontological engineering. To date, we have proposed OMNIBUS, an ontology that comprehensively covers different learning/instructional theories and paradigms, and SMARTIES, a theory-aware and standards-compliant authoring system to create learning/instructional scenarios based on OMNIBUS. This approach was intended to bridge the gap between theory and practice in scientific and technological development, including learning/instruction support. The goals of this study included the following: that computers would (a) understand a variety of learning/instructional theories based on their organization, (b) utilize such understanding to help authors build learning/instructional scenarios, and (c) make such theoretically sound scenarios interoperable within the framework of technology standards. This paper suggests an ontological engineering solution to achieve these three goals and describes the implementation and feasibility demonstrations of the basic functions of SMARTIES, a solution that supports the design of learning/instructional scenarios based on multiple theories. Although the evaluation is far from complete in terms of practical use, we believe that the results of this study speak to high-level technical challenges of ITS authoring systems and the other areas of AIED, and therefore constitute a substantial contribution.
    International Journal of Artificial Intelligence in Education 01/2009; 19:211-252.
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    Yusuke Hayashi · Seiji Isotani · Jacqueline Bourdeau · Riichiro Mizoguchi
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    ABSTRACT: Many instructional design models have been proposed and their benefits are evident. However, there is lack of a common and formal notation to describe the product of the design. This causes difficulty in evaluating the product (the course) in the development. To eliminate the difficulty, we need a formal framework which has enough semantics for keeping the consistency of the product. Thus, this work aims at proposing a unified modeling framework for learning and instruction based on ontologies that has the potential to support some phases of instructional design. Furthermore, we give an example of how one-to-one instruction and collaborative learning are modeled on the proposed framework.
    Education and Technology for a Better World, 9th IFIP TC 3 World Conference on Computers in Education, WCCE 2009, Bento Gonçalves, Brazil, July 27-31, 2009. Proceedings; 01/2009
  • Yusuke Hayashi · Jacqueline Bourdeau · Riichiro Mizoguch
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    ABSTRACT: In spite of the fact that the relation between theory and practice is a foundation of scientific and technological development, the trend of increasing the gap between theory and practice accelerates in these years. The gap embraces a risk of distrust of science and technology. Ontological engineering as the content-oriented research is expected to contribute to the resolution of the gap. This paper presents the feasibility of organization of theoretical knowledge on ontological engineering and new-generation intelligent systems based on it through an application of ontological engineering in the area of learning/instruction support. This area also has the problem of the gap between theory and practice, and its resolution is strongly required. So far we proposed OMNIBUS ontology, which is a comprehensive ontology that covers different learning/instructional theories and paradigms, and SMARTIES, which is a theory-aware and standard-compliant authoring system for making learning/instructional scenarios based on OMNIBUS ontology. We believe the theory-awareness and standard-compliance bridge the gap between theory and practice because it links theories to practical use of standard technologies and enables practitioners to easily enjoy theoretical support while using standard technologies in practice. The following goals are set in order to achieve it; computers (1) understand a variety of learning/instructional theories based on the organization of them, (2) utilize the understanding for helping authors' learning/instructional scenario making and (3) make such theoretically sound scenarios interoperable within the framework of standard technologies. This paper suggests an ontological engineering solution to the achievement of these three goals. Although the evaluation is far from complete in terms of practical use, we believe that the results of this study address high-level technical challenges from the viewpoint of the current state of the art in the research area of artificial intelligence not only in education but also in general, and therefore we hope that constitute a substantial contribution for organization of theoretical knowledge in many other areas.
    Transactions of the Japanese Society for Artificial Intelligence 01/2009; 24:351-375. DOI:10.1527/tjsai.24.351
  • Yusuke Hayashi · Jacqueline Bourdeau · Riichiro Mizoguchi
    [Show abstract] [Hide abstract]
    ABSTRACT: This paper describes the achievements of an innovative eight-year research program first introduced in Mizoguchi and Bourdeau (2000), which was aimed at building a theory-aware authoring system by using ontological engineering. To date, we have proposed OMNIBUS, an ontology that comprehensively covers different learning/instructional theories and paradigms, and SMARTIES, a theory-aware and standards-compliant authoring system to create learning/instructional scenarios based on OMNIBUS. This approach was intended to bridge the gap between theory and practice in scientific and technological development, including learning/instruction support. The goals of this study included the following: that computers would (a) understand a variety of learning/instructional theories based on their organization, (b) utilize such understanding to help authors build learning/instructional scenarios, and (c) make such theoretically sound scenarios interoperable within the framework of technology standards. This paper suggests an ontological engineering solution to achieve these three goals and describes the implementation and feasibility demonstrations of the basic functions of SMARTIES, a solution that supports the design of learning/instructional scenarios based on multiple theories. Although the evaluation is far from complete in terms of practical use, we believe that the results of this study speak to high-level technical challenges of ITS authoring systems and the other areas of AIED, and therefore constitute a substantial contribution.
    International Journal of Artificial Intelligence in Education 01/2009; 19(2):211-252.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Structuring learning/instructional theories suffers from the issue of "paradigms", which makes it even more challenging. This paper discusses the conceptualization of theories/models and proposes a mechanism to provide perspectives for understanding and utilizing them. Two types of conceptualization proposed in this paper reveal their characteristics from a variety of viewpoints.