Abstract
This study presents a hybrid methodology for solving the serious game design evaluation in which evaluation criteria are based on meaningful learning, ARCS motivation, cognitive load, and flow theory (MACF) by rough set theory (RST) and experts’ selection. The purpose of this study tends to develop an evaluation model with RST based fuzzy Delphi-AHP-TOPSIS for MACF characteristics. Fuzzy Delphi method is utilized for selecting the evaluation criteria, Fuzzy AHP is used for analyzing the criteria structure and determining the evaluation weight of criteria, and Fuzzy TOPSIS is applied to determine the sequence of the evaluations. A real case is also used for evaluating the selection of MACF criteria design for four serious games, and both the practice and evaluation of the case could be explained. The results show that the playfulness (C24), skills (C22), attention (C11), and personalized (C35) are determined as the four most important criteria in the MACF selection process. And evaluation results of case study point out that Game 1 has the best score overall (Game 1 > Game 3 > Game 2 > Game 4). Finally, proposed evaluation framework tends to evaluate the effectiveness and the feasibility of the evaluation model and provide design criteria for relevant multimedia game design educators.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.