Toward a Taxonomy Linking Game Attributes to Learning
| Autor: | Davin Pavlas, Kyle Heyne, Elizabeth H. Lazzara, Eduardo Salas, Wendy L. Bedwell |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Knowledge management
Computer science Game design document Instructional design business.industry ComputingMilieux_PERSONALCOMPUTING Educational technology General Social Sciences Computer Science Applications Subject-matter expert Empirical research Card sorting Taxonomy (general) Game Developer business |
| Zdroj: | Simulation & Gaming. 43:729-760 |
| ISSN: | 1552-826X 1046-8781 |
| DOI: | 10.1177/1046878112439444 |
| Popis: | The serious games community is moving toward research focusing on direct comparisons between learning outcomes of serious games and those of more traditional training methods. Such comparisons are difficult, however, due to the lack of a consistent taxonomy of game attributes for serious games. Without a clear understanding of what truly constitutes a game, scientific inquiry will continue to reveal inconsistent findings, making it hard to provide practitioners with guidance as to the most important attribute(s) for desired training outcomes. This article presents a game attribute taxonomy derived from a comprehensive literature review and subsequent card sorts performed by subject matter experts (SMEs). The categories of serious game attributes that emerged represent the shared mental models of game SMEs and serve to provide a comprehensive collection of game attributes. In order to guide future serious games research, the existing literature base is organized around the framework of this taxonomy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|