scholarly journals Developing Ideation Cards for Mixed Reality Game Design

2017 ◽  
Vol 3 (2) ◽  
Author(s):  
Richard Wetzel ◽  
Tom Rodden ◽  
Steve Benford
Keyword(s):  
Collaborative Design ◽  
Game Design ◽  
Design Space ◽  
Mixed Reality ◽  
Idea Generation ◽  
Physical World ◽  
Pervasive Games ◽  
Domain Specific ◽  
Iterative Development ◽  
Different Types

Mixed reality games (MRGs) encompass a variety of gaming genres such as pervasive games, location-based games, and augmented reality games. They enrich the physical world with technology to create new and exciting possibilities for games – but at the same time introduce new challenges. In order to make the vast design space of MRGs easily accessible we have developed our Mixed Reality Game Cards. These are a deck of ideation cards that synthesize design knowledge about MRGs and enable collaborative design in a playful manner. In this paper, we describe the iterative development of the Mixed Reality Game Cards over the course of six studies. The final version of the cards constitutes a helpful tool for future designers of MRGs both for rapid idea generation as well as for more in-depth idea development. We achieve this by utilizing different types of domain-specific cards (Opportunities, Questions, Challenges) as well as promoting the inclusion of domain-extrinsic Theme cards and suggesting different rules for interacting with the cards.

scholarly journals Bayesian Network Classifiers for Set-Based Collaborative Design

2012 ◽  
Vol 134 (7) ◽  
Author(s):  
David W. Shahan ◽  
Carolyn Conner Seepersad
Keyword(s):  
Bayesian Network ◽  
Collaborative Design ◽  
Design Problem ◽  
Design Space ◽  
Expert Knowledge ◽  
Optimization Techniques ◽  
Domain Specific ◽  
Bayesian Network Classifiers ◽  
New Information ◽  
Engineering Design Problems

Complex engineering design problems are often decomposed into a set of interdependent, distributed subproblems that are solved by domain-specific experts. These experts must resolve couplings between the subproblems and negotiate satisfactory, system-wide solutions. Set-based approaches help resolve these couplings by systematically mapping satisfactory regions of the design space for each subproblem and then intersecting those maps to identify mutually satisfactory system-wide solutions. In this paper, Bayesian network classifiers are introduced for mapping sets of promising designs, thereby classifying the design space into satisfactory and unsatisfactory regions. The approach is applied to two example problems—a spring design problem and a simplified, multilevel design problem for an unmanned aerial vehicle (UAV). The method is demonstrated to offer several advantages over competing techniques, including the ability to represent arbitrarily shaped and potentially disconnected regions of the design space and the ability to be updated straightforwardly as new information about the satisfactory design space is discovered. Although not demonstrated in this paper, it is also possible to interface the classifier with automated search and optimization techniques and to combine expert knowledge with the results of quantitative simulations when constructing the classifiers.

scholarly journals Mixed Reality Entertainment and Art

2009 ◽  
Vol 8 (2) ◽  
pp. 83-90 ◽  
Author(s):  
Adrian David Cheok ◽  
Michael Haller ◽  
Owen Noel Newton Fernando ◽  
Janaka Prasad Wijesena
Keyword(s):  
Social Interaction ◽  
Design Space ◽  
Mixed Reality ◽  
Physical World ◽  
Next Generation ◽  
Game World ◽  
Physical Interactions ◽  
Virtual Game

Social and physical interactions are new paradigms that outline the vision of the next generation of entertainment. We can provide these interactions through employment of technologies such as mixed reality to merge the human physical world with the virtual game world. However, there are a few obstacles in achieving physical, mobile, tangible and social interaction for people's entertainment. The authors had organized a workshop on this topic of "Mixed Reality Entertainment and Art" at the ISMAR 2007 conference in Nara, and the presentations are summarized in this paper. Furthermore, the authors detail their related systems, including BlogWall, MediaMe, and Shared Design Space to provide artistic and entertainment mixed reality.

scholarly journals Transforming a Theoretical Framework to Design Cards: LEAGUE Ideation Toolkit for Game-Based Learning Design

2020 ◽  
Vol 12 (20) ◽  
pp. 8487
Author(s):  
Rabail Tahir ◽  
Alf Inge Wang
Keyword(s):  
Design Process ◽  
Collaborative Design ◽  
Game Design ◽  
Idea Generation ◽  
Educational Game ◽  
Design Practice ◽  
Game Based Learning ◽  
Complex Process ◽  
Integrate Research ◽  
Early Design Phase

Educational game design is a complex process demanding multi-dimensional focus in a heterogeneous team to balance multiple aspects. The existing Game-based learning (GBL) frameworks detail the required knowledge but are hard to use in design practice. Conversely, card-based design tools are a lightweight approach used to assist the early design phase. While several game design cards exist, none is specific for informing GBL knowledge. There is a lack of operationalizable approaches for designing learning games that integrate research based GBL knowledge into the actual ideation process. This paper presents a card-based GBL ideation toolkit to reduce the complexity of framework application and introduction of key GBL concepts in the design process as a tangible reference point to facilitate multi-dimensional focus, supporting idea generation, critical reflection, and creation of a shared understanding in the collaborative design process. The paper describes a ten-step process of transforming the LEAGUE framework into the LEAGUE toolkit (GBL ideation cards), an evaluation of the toolkit with design workshop participants, and design lessons detailing strengths and limitations to support GBL design practices.

Sequential Sampling With Kernel-Based Bayesian Network Classifiers

2011 ◽  
Author(s):  
David Shahan ◽  
Carolyn C. Seepersad
Keyword(s):  
Bayesian Network ◽  
Collaborative Design ◽  
Design Space ◽  
Sequential Sampling ◽  
Space Filling ◽  
Training Set ◽  
Design Problems ◽  
Sampling Schemes ◽  
Domain Specific ◽  
Bayesian Network Classifiers

Complex design problems are typically decomposed into smaller design problems that are solved by domain-specific experts who must then coordinate their solutions into a satisfactory system-wide solution. In set-based collaborative design, collaborating engineers coordinate themselves by communicating multiple design alternatives at each step of the design process. Previous research has demonstrated that classifiers can be a communication medium for facilitating set-based collaborative design because of their ability to divide a design space into satisfactory and unsatisfactory regions. The proposed kernel-based Bayesian network (KBN) classifier uses a set of example designs of known acceptability, called the training set, to create a map of the satisfactory region of the design space. However, previous implementations used deterministic space-filling sampling sequences to choose the training set of designs. The shortcoming of deterministic space-filling sampling schemes is that they do not adapt to focus the samples on regions of interest to the design team (exploitation) or, alternatively, on regions in which little information is known (exploration). In this paper, we introduce the use of KBN classifiers as the basis for sequential sampling strategies that can be exploitive, exploratory, or any combination thereof.

Les représentations des enfants de 5-6 ans sur la fusion et la solidification du sel, comme support pour le déploiement des activités didactiques

2015 ◽  
Vol 6 (3) ◽  
pp. 943-947 ◽  
Author(s):  
Konstantinos Ravanis
Keyword(s):  
Young Children ◽  
Empirical Research ◽  
School Children ◽  
Physical World ◽  
Scientific Model ◽  
Open Type ◽  
Different Types ◽  
Individual Conversations ◽  
Melting And Solidification

The representation of the properties and phenomena of the physical world exists from the beginning of life, as a first datum of reality. In several studies focused on children's representations we find that these representations these representations are critical to education and are often incompatible with the scientific model. This article presents the results of an empirical research on the representations of young children for melting and solidification of salt. The research sample consisted of 79 pre-school children (five to six years old) from one state kindergarten in Greece. Data were collected through expanded, open type, semi-structured individual conversations between a child of the sample and one researcher. The results of the interviews show that these children use different types of representations, the majority dominated by the nature of the substance under study.

scholarly journals Creativity as a function of problem-solving expertise: posing new problems through investigations

ZDM ◽  
2021 ◽  
Author(s):  
Haim Elgrably ◽  
Roza Leikin
Keyword(s):  
Problem Solving ◽  
Dynamic Geometry ◽  
Problem Posing ◽  
Dynamic Geometry Environment ◽  
Mathematics Majors ◽  
Individual Interviews ◽  
University Mathematics ◽  
Domain Specific ◽  
Mathematics Test ◽  
Different Types

AbstractThis study was inspired by the following question: how is mathematical creativity connected to different kinds of expertise in mathematics? Basing our work on arguments about the domain-specific nature of expertise and creativity, we looked at how participants from two groups with two different types of expertise performed in problem-posing-through-investigations (PPI) in a dynamic geometry environment (DGE). The first type of expertise—MO—involved being a candidate or a member of the Israeli International Mathematical Olympiad team. The second type—MM—was comprised of mathematics majors who excelled in university mathematics. We conducted individual interviews with eight MO participants who were asked to perform PPI in geometry, without previous experience in performing a task of this kind. Eleven MMs tackled the same PPI task during a mathematics test at the end of a 52-h course that integrated PPI. To characterize connections between creativity and expertise, we analyzed participants’ performance on the PPI tasks according to proof skills (i.e., auxiliary constructions, the complexity of posed tasks, and correctness of their proofs) and creativity components (i.e., fluency, flexibility and originality of the discovered properties). Our findings demonstrate significant differences between PPI by MO participants and by MM participants as reflected in the more creative performance and more successful proving processes demonstrated by MO participants. We argue that problem posing and problem solving are inseparable when MO experts are engaged in PPI.

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