Mixed Reality Games

Mixed Reality Games

Jean-Charles Marty (LIRIS, UMR5205, F69621, Université de Lyon, France & Université de Savoie, France), Thibault Carron (LIP6, UMR7606, Sorbonne Universites, Paris 6, France & Université de Savoie, France), Philippe Pernelle (DISP Lab, Université de Lyon, Lyon, France), Stéphane Talbot (Université de Savoie, Chambéry, France) and Gregory Houzet (Imep-Lahc Lab, Université de Savoie, Chambéry, France)
Copyright: © 2015 |Pages: 15
DOI: 10.4018/ijgbl.2015010103


The authors research work deals with the development of new game-based learning (gbl) environments. They think that the way of acquiring knowledge during a learning session is similar to following an adventure in a role-playing game and they apply the metaphor of exploring a virtual world, where each student embarks on a quest in order to collect knowledge related to a learning activity. In their university, the authors have set up numbers of experiments with students using gbl environments. They revealed weaknesses for specific learning activities. Sometimes, learners seem to acquire a skill in the game, but they are not able to reuse it easily in the real world. This is particularly the case for skills that require concrete manipulation of real objects to be acquired. Gbl environments thus lack of means to learn know-how aspects. Some of the learning processes involving real world objects are very difficult to reproduce in gbl environments and there is an essential technological issue in mixing virtual and real aspects in gbl environments. In this article, the authors describe the possible problems that can appear when using this mixed approach, give hints on how to avoid them and illustrate the proposition with examples issued from the electronic domain. The authors focus on issues linked to the transition between virtual and real worlds and they explore how new electronic features can facilitate this mixed approach, where identification, localisation and update of the user models are key issues.
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Due to their large educational features, Learning Games are currently spreading out (Squire, 2003) (Bogost, 2007). Indeed, they are used for science teaching (Muratet et al., 2012)(Parry et al, 2008), language (Wagner et al., 2003), history (Schrier, 2006). We can also cite more recent and promising ones that are close to commercial standing (very accessible) and less research work: Blockly Maze, Refraction, Prog&Play or Dragon Box. Both industrial and academic institutions want to use them in order to have motivating and flexible environments to train their employees / students (Ouhlaci et al., 2013)(Pernelle et al., 2013). The complexity of Learning Games development is thus increasing significantly, since lots of new needs and possibilities appear (Whitton, 2009): new up-to-date functionalities are often wanted: collaborative aspects, observation features for awareness purpose, and links to tangible user interfaces, less expensive, interoperability with other devices, easy access, support for metacognition (Dimitracopoulou, 2005). The requirements for these learning environments imply building several components aiming at supporting specific activities (games of “snakes and ladders” type, puzzles, animated MCQs, mimicry, alea, racing game, time trial) (Djaouti, 2008) (Mariais, 2009). Some of them may be used as competitive, collaborative or even “coopetitive” ones (Asaro, 2010)(Henrysson et al., 2005).

In light of this observation, there is an obvious need for realistic and reliable assessment about students’ skills, actions or behaviours especially for the teacher (Felicia, 2009). Indeed, for certain specific domains, the teacher needs to evaluate his/her pedagogical session according to several points and some are particularly difficult to assess with such learning environments. Certain domains present for example the particularity of exhibiting both theoretical knowledge and practical know-how (operations in manufacturing or medicine, for example) (George and Serna, 2011). For such contexts, the current Learning Games are not efficient enough concerning this second point: a unique and full digitalisation of the objects alone is not sufficient to guarantee both effective learning and assessment of the techniques (Schrier, 2006): in such cases, it is mandatory to come back to the real world and thus develop a mixed-reality learning game.

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