Enhanced value benefit analysis of game frameworks as a tool for digital serious game development

When creating a digital serious game the major challenges are how to ensure the right balance between engagement (as defined by Prensky 2007) and learning as well as how to find the best fitting underlying game framework or engine. Whereas the former is of theoretical nature and involves the actual game design and specification the latter is the limiting technical factor and essentially the user interface with what the users actually see. The selection of a game framework can have severe implications how the serious game is realized. Typically the learning objectives and the game design concept are defined at first then a game framework is chosen which optimally supports the specifications and requirements. But this decision process is not standardized neither exist guidelines on how to optimally choose the best fitting game framework. This paper presents a workflow and toolset on how to match your learning objectives and game design requirements on a game framework with optimal support for the right balance between engagement and learning. The approach presented in this paper is based upon a generic model of a value benefit analysis. The model is enhanced by a matrix which encodes the evaluation of a game framework not only by its value for the individual game design needs but especially for the individual didactic value. The model enables decisions on subjective factors for this multidimensional evaluation issue. It does not present a tool to generate an impartial general ranking list of game frameworks for serious games. It is a tool for serious game developers to have a subjective individual list of game frameworks fitting their individual needs of technical requirements and didactic motivation. The basic concept and strategy behind the approach are presented as well as an application example. This paper presents and discusses a hierarchy of general criteria for developing a serious game which can be used to evaluate a framework within the model. The criteria are divided into main and interleaved sub criteria. The paper also discusses the weighting of criteria and the used cardinal scale for criteria and weighting. Finally the paper comments on the matrix which will consider the didactic needs. With the described approach developers of serious games will have a workflow on how to find a suitable game framework with regard to the defined game design and didactics