Gamification, recently considered as a science, takes advantage of the benefits of games to induce desirable behaviors in a given “normal” activity. When applied in education, it is an approach to motivate and engage students in their learning process by incorporating game design principles. This paper presents the design and deployment of a game conducted in parallel with two groups of the engineering course “operations research”. The game design is theoretically supported, and unlike literature, the game proposed has the main distinguishing features: (a) it is carried out in parallel with the standard course, where player participation is optional, with extrinsic motivators regarding the final grade, (b) it lasts the entire semester, and it was applied to different groups with the same instructor, (c) in addition to academic performance, it has other social relatedness desired outcomes, (d) it combines the use of specific game elements divided in three types of activities: Mastery, related to the core topics of the class, Institutional, related to the university life and community, and Teamwork activities; and (e) it uses a WhatsApp chat group as the common communication platform. The assessment is twofold: the effects on learning, measured in two indicators, failure rate and average grade; and the perception of the game itself. Statistical results present empirical evidence of the positive effects of gamification on academic performance and other desired behaviors of social relatedness, such as a sense of belonging and teamwork.
The improvement of transport and logistics performance of Emergency Medical Services (EMSs) systems has been mainly addressed through mathematical modelling, operations research, and simulation methods. This paper proposes an alternative and/or complementary improvement approach based on the adaptation and simultaneous deployment of lean thinking and Theory of Constraint (TOC) methods and tools. The paper briefly reviews key aspects of the application of lean in the logistics and healthcare industries and conceptually develops the proposed lean-TOC approach. The approach is then tested, through an individual detail case study, in the EMS transport and logistic system of the Red Cross operating in the metropolitan area of Monterrey, Mexico. The results obtained from the case study suggest that the proposed systematic lean-TOC approach may be an effective alternative and/or complement to mathematical modelling, operations research, and simulation methods to improve EMS transport and logistics operations.
PurposeThe objective of this paper is to assess and synthesize the published literature related to the application of data analytics, big data, data mining and machine learning to healthcare engineering systems.Design/methodology/approachA systematic literature review (SLR) was conducted to obtain the most relevant papers related to the research study from three different platforms: EBSCOhost, ProQuest and Scopus. The literature was assessed and synthesized, conducting analysis associated with the publications, authors and content.FindingsFrom the SLR, 576 publications were identified and analyzed. The research area seems to show the characteristics of a growing field with new research areas evolving and applications being explored. In addition, the main authors and collaboration groups publishing in this research area were identified throughout a social network analysis. This could lead new and current authors to identify researchers with common interests on the field.Research limitations/implicationsThe use of the SLR methodology does not guarantee that all relevant publications related to the research are covered and analyzed. However, the authors' previous knowledge and the nature of the publications were used to select different platforms.Originality/valueTo the best of the authors' knowledge, this paper represents the most comprehensive literature-based study on the fields of data analytics, big data, data mining and machine learning applied to healthcare engineering systems.
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