Exploring Systems Performance Using Modeling and Simulation – Project-based Study and Teaching

Modeling and Simulation (M&S) provides a risk-free environment allowing the users to experiment in a computer-generated virtual platform and analyze the what-if scenarios for effective decision support systems. Due to its pervasive usefulness, the concept of M&S is widely used across many sectors, including manufacturing, warehouse operations, supply chain, logistics, transportation, mining, and many more. The field of M&S requires computer-intensive and software-based training, which is very different from teaching in a regular classroom setting. Hence, we develop a three-stage (mimic-guide-scaffold) project-based teaching strategy to enhance students learning experience in M&S education. Here, students first follow the instructor to understand basics of simulation and become familiar with AnyLogic software. Second, the students work on a group project under the passive supervision of the instructor to enhance their problem-solving capability. In the third step, students work independently on a similar but extensive project to scaffold their knowledge. The project was designed to answer three high-level key research questions for a hospital system including systems throughput, resource utilization, and patients’ length of stay reduction. We performed a thorough evaluation using an anonymous survey, where thirty-one students participated to provide their feedback. This paper provides a detailed description of the projects including problem statements, learning objectives, evaluation rubrics, data collection criteria, and evaluation outcomes with detailed discussion

Realism of Simulation Models in Serious Gaming: Two case studies from Urban Water Management Higher Education

For games used in educational contexts, realism, i.e., the degree of congruence between the simulation models used in the games and the real-world systems represented, is an important characteristic for achieving learning goals well. However, in the past, the realism of especially entertainment games has often been identified as insufficient. Thus, this study is investigating the degree of realism provided by current games. To this purpose, two games in the domain urban water management, a subdomain of environmental engineering (EE), are examined. One is ANAWAK, a web-based serious game on water management and climate change. For ANAWAK, an analysis of the simulation model is conducted. Second, the simulation model of the entertainment game Cities: Skylines (CS) is analyzed. In addition, a survey among CS players (N=61) is conducted. Thereby, different degrees of realism in various EE subdomains are revealed. All in all, there are still considerable deficits regarding the degree of realism in the CS simulation model. However, modding as a means of achieving more realistic simulation models is more widely supported than in the past

CDIO-CT collaborative strategy for solving complex STEM problems in system modeling and simulation: an illustration of solving the period of mathematical pendulum

The problem-project-oriented STEM education plays a significant role in training students' ability of innovation. Although the conceive-design-implement-operate (CDIO) approach and the computational thinking (CT) are hot topics in recent decade, there are still two deficiencies: the CDIO approach and CT are discussed separately and a general framework of coping with complex STEM problems in system modeling and simulation is missing. In this paper, a collaborative strategy based on the CDIO and CT is proposed for solving complex STEM problems in system modeling and simulation with a general framework, in which the CDIO is about ``how to do", CT is about ``how to think", and the project means ``what to do". As an illustration, the problem of solving the period of mathematical pendulum (MP) is discussed in detail. The most challenging task involved in the problem is to compute the complete elliptic integral of the first kind (CEI-1). In the philosophy of STEM education, all problems have more than one solutions. For computing the CEI-1, four methods are discussed with a top-down strategy, which includes the infinite series method, arithmetic-geometric mean (AGM) method, Gauss-Chebyshev method and Gauss-Legendre method. The algorithms involved can be utilized for R & D projects of interest and be reused according to the requirements encountered. The general framework for solving complex STEM problem in system modeling and simulation is worth recommending to the college students and instructors.Comment: 27 pages, 12 figures, 11 table