This paper presents findings from the use of a simulation learning environment to teach college students about principles of accumulation. The simulation package is part of an ongoing study testing the utility of systems simulations for teaching students about the complex systems relationships in environmental studies and science. We have conducted paired experiments over the past five semesters in a team-taught, college-level Introduction to Environmental Science course using system dynamics simulations. We have progressively refined the systems learning objectives, simulations, and assessments. The focus that has emerged from this research is the need for building systems understanding about the dynamics of accumulations. While most students are able to define and identify everyday examples of accumulations, they have difficulty understanding relationships between flows and accumulations in any but the simplest cases. The pattern-matching tendency is strong. In this paper we present a simulation developed specifically to address simple issues of accumulation and discuss lessons we have learned about best practices for discovery learning in this setting.
This poster presents a web-based simulation learning environment for facilitating discovery learning about accumulations. It was designed to complement an Introduction to Environmental Science course at the college level, but will eventually be available as a stand-alone package. The primary learning objective is to develop the users understanding of the relationship between inflows, outflows, and accumulations, as well as the effect of changes in inflow and outflow rates. Results from the use of this simulation in freshman Environmental Science classes will be presented in another paper. Here we describe the domain and discovery learning objectives, storyboard, and interpretive scaffolding of the simulation learning package, and present insights from user feedback on the design. We plan to have a demonstration version of the simulation available at the conference.
Joining the European Union big opportunities in the international markets have opened for Latvia. Paper purpose is to investigate influence of international integration processes on development of economy of Latvia. Latvia's incoming in EU increased the amount of received means from structural and cohesion funds, removed the trading barriers, increases foreign investments, reduced unemployment and increased labor migration. In the paper the system dynamics model, which describes integration of the Latvian economy into EU, is developed. In the model international financial flows connected with Latvia and EU; import, its relation to internal producing; and migration processes are considered. Model functioning is measured considering various scenarios of situation development. The developed model can be used not only in the analysis of Latvias economic integration in the EU, but on its basis it is possible to create models of regional cohesion in Europe.
This paper explores the dynamics of energy reduction policy setting for data centers in the face of new metrics and related regulation. With these new metrics there is a potential for management to establish policies that achieve the specific metric target while sub-optimizing the total energy reduction opportunity. This paper will address the question of whether new insight can be gained by using a system dynamics approach versus static return on investment forecasting. The first part of this paper will describe the unique dynamics of energy consumption in a data center and the application of one particular metric used to indicate energy consumption efficiency. The second part of this paper proposes a model that represents the interconnected behavior of data center energy consumption and metric based policy implementation. This approach is compared to static methods and the insights gained from taking a systems approach.
In this study, a dynamic simulation model for thyroid hormone system is constructed. The objective of this work is to first generate the dynamics of the hormones involved in thyroid hormone system in healthy body, and then to adapt the model to portray the dynamics of certain common thyroid disorders. The ultimate aim is to provide a platform to conduct scenario analyses without risking patients health. Thyrotropin-releasing hormone (TRH), thyroid-stimulating hormone (TSH), thyroid hormones, weights of hypothalamus, pituitary and thyroid gland are the basic variables in the model. Scenario experiments are simulated and outputs consistent with the data in literature, both qualitative and quantitative, are obtained. As future work, the model will be extended to cover more disorders and the parameter values will be more realistically calibrated.