Bulletin of the American Physical Society
2017 Annual Spring Meeting of the APS Ohio-Region Section
Volume 62, Number 6
Friday–Saturday, May 5–6, 2017; Ypsilanti, Michigan
Session A1: Invited: Computational Physics I |
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Chair: Ernest Behringer, Eastern Michigan University Room: Pray-Harrold 201 |
Friday, May 5, 2017 2:15PM - 3:00PM |
A1.00001: The statistical physics of networks Invited Speaker: Mark Newman There are networks in every part of our lives: the Internet, the power grid, the road network, networks of friendship or acquaintance, ecological networks, biochemical networks, and many others. As large-scale data on these networks have become available in the last few years, a new science of networks has grown up combining observations and theory and drawing heavily on ideas from physics, to shed light on systems ranging from bacteria to the whole of human society. This talk will give an introduction to this rapidly-growing interdisciplinary branch of science and discuss some of the latest discoveries in the field. [Preview Abstract] |
Friday, May 5, 2017 3:00PM - 3:45PM |
A1.00002: How might Physics Education Research facilitate the coming computational revolution? Invited Speaker: Marcos Caballero Computation has revolutionized how modern science is done. Modern scientists use computational techniques to reduce mountains of data, to simulate impossible experiments, and to develop intuition about the behavior of complex systems. Much of the research completed by modern scientists would be impossible without the use of computation. And yet, while computation is a crucial tool of practicing scientists, most modern science curricula do not reflect its importance and utility. In this talk, I will discuss the urgent need to construct such curricula in physics and present research that investigates the challenges at a variety of all scales -- from the largest (institutional structures) to the smallest (student understanding of a concept). I will discuss how the results of this research can be leveraged to facilitate the computational revolution. This research will help us understand and develop institutional/departmental incentives, effective teaching practices, evidence-based course activities, and valid assessment tools. [Preview Abstract] |
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