Sammanfattning
The distinction between implicit and unselfconscious design cultures on one hand andexplicit, self-conscious design cultures on the other provides a principle for interrelating avariety of game design approaches within a coherent game design meta-model. The designapproaches in order of increasing design self-consciousness include implicit design,‘cookbook’ design methods, taxonomy and ontology-based game design, theory-driven designand formalist reflexive design. Implicit design proceeds by copying existing examples ofgame designs, while ‘cookbook’ methods generalize from examples to create lists of designheuristics. Taxonomy and ontology-based game design is based upon more systematic modelsof the types, features, elements, structure and properties of games. The theory-driven levelinvolves the design of game systems to facilitate game play motivated by cognitive, scientificand/or rhetorical theories of game affect and functionality, or incorporating technicalinnovations providing the basis for new game mechanics and experiences. The formalist levelrepresents the application of reflexive contemporary artistic perspectives to games, resultingin games that reflect upon, question or reveal game form. In placing these differentapproaches within a hierarchy of increasing self-consciousness of design practices, the meta-model provides a clear account of the roles of research and artistic methods in game designand innovation, providing a foundation for more explicit design decision making and gameeducation curriculum development integrated with higher-level research.
Originalspråk | Engelska |
---|---|
Titel på värdpublikation | Extending Experiences |
Undertitel på värdpublikation | Structure, analysis and design of computer game player experience |
Redaktörer | Olli Leino, Hanna Wirman, Amyris Fernandez |
Förlag | University of Lapland Press |
Sidor | 250-272 |
ISBN (elektroniskt) | 978 - 952-484- 440-6 |
ISBN (tryckt) | 978-952-484-197-9 |
Status | Publicerad - 2008 |
Externt publicerad | Ja |
Nationell ämneskategori
- Datavetenskap (10201)