3-abstract

ABSTRACTS

TEACHING NETWORK SCIENCE TO UNDERGRADUATES

Chris Arney, Kate Coronges

United States Military Academy West Point

Establishing new curricula can be challenging. Many educational issues need to be solved in addition to developing new courses and convincing the administration and colleagues of the need for and the role of the new program. This is especially challenging when your school is possibly the first one trying to build such a program. This presentation will describe the undergraduate academic minor in Network Science (NS) at United States Military Academy. In addition to presenting information about this academic program, this talk will discuss recently offered interdisciplinary NS courses. These courses teach students to confront complexity and non-reductivity in modeling, solving, analyzing, and understanding large dynamic networks. The courses contain a mix of theory and application, where students are asked to apply network strategies and measures for models to benefit society in the physical, social, and informational sciences. Since evaluating and recommending policy is a complex social, political, scientific process with many competing issues and challenges, these courses are often team taught. In addition, the related efforts to develop student interest and engagement in NS through an international modeling contest are presented.

NETWORKS OUTREACH IN SCHOOLS

Mason Alexander Porter, University of Oxford

I will describe ongoing efforts to conduct outreach efforts in schools in the UK. I'll introduce some of the materials that we've developed and indicate some ideas for future development. I hope to encourage similar efforts across the world.

SOCIAL DIFFUSION AND GLOBAL DRIFT IN ADAPTIVE SOCIAL NETWORKS

Hiroki Sayama

Collective Dynamics of Complex Systems Research Group, Binghamton University

Center for Complex Network Research, Northeastern University

Abstract : Social contagion has been studied in various contexts. Many instances of socialcontagion can be modeled as an infection process where a specific state (adoption of product, fad, knowledge, behavior, etc.) spreads from individual to individual through links between them. In the meantime, other forms of social contagion may better be understood as a diffusion process where the state of an individual tends to assimilate with the social norm (i.e., local average state) within his/her neighborhood. Unlike infection scenarios where influence is nonlinear, unidirectional, fast, and potentially disruptive, social diffusion is linear, bidirectional, gradual, and converging. The distance between an individual's state and his/her neighbors' average state always decreases, and thus a homogeneous global state is guaranteed to be the network's stable equilibrium state in the long run. This does not sound as intriguing or exciting as infection dynamics, which might be why there are very few studies on mathematical models of social diffusion processes.Here, this study attempts to shed new light on an unrecognized characteristic of social diffusion, i.e., non-trivial drift it can cause to the network's global average state. Although somewhat counterintuitive, such global drift is indeed possible because, unlike physical diffusion processes, social diffusion processes are *not* conservational. We present a mathematical model of social diffusion to study the mechanism of this phenomenon, and some possible collective actions for influencing the direction of global drift will be proposed. The relevance of social diffusion to individual and collective improvement will be discussed, with an emphasis on educational applications.

CHALLENGES, CHANGES, AND CHURN: A LONGITUDINAL SOCIAL NETWORK PERSPECTIVE OF URBAN DISTRICT LEADERSHIP

Alan J. Daly, University of California, San Diego

Kara Finnigan, University of Rochester

Yi-Hwa Liou, University of California, San Diego

Educational leadership has been repeatedly identified as important both in terms of organizational outcomes and improving achievement. In high performing systems the educational leadership literature also suggests the importance of coherence and alignment across a district in implementing large-scale change and improvement. However, despite the well documented importance of coherence and consistency, urban districts across the country routinely turnover almost 30% of leaders in a given year. The effects of this turnover have been associated with a variety of negative outcomes including increased costs and decreased performance. In this presentation we argue that exploring and understanding churn from a network perspective is critical as beyond fiscal and human capital costs there are significant social capital costs to a system associated with both the exit of individuals (loss of knowledge, social support, organizational memory, training and development costs) as well as the entrance of new actors (on boarding, training, learning both technical and social system). In this exploratory case study of a large urban district we focus on social network churn drawing on three years of social network data between district office and site leaders. We explore the challenges in urban district leadership, changes undertaken in improving outcomes, and the networkchurn in the system in response to both challenges and changes. This work highlights the dynamic nature of social relationships and pushes beyond more static assessments of social networks.

INTERVENTIONS IN NETWORK THINKING: CASE STUDIES FROM AFTER-SCHOOL PROGRAMS SERVING AFFLUENT AND IMPOVERISHED STUDENTS

Brooke Foucault Welles, Northeastern University

“Network Thinking,” or being able to accurately recognize and reason about the resources within one’s own social network may afford young people a number of benefits including greater educational attainment, earlier career success, improved physical health, and stronger emotional resilience through transitions. Although young people naturally vary in their abilities to understand and leverage their social networks, I believe that like many other social-cognitive skills, Network Thinking can be improved through training. In this talk, I will report preliminary results of a project designed to evaluate a Network Thinking intervention for adolescents ages 12-17. Specifically, I will compare and contrast my experiences working with groups of affluent and impoverished teens, highlighting the different challenges and benefits of discussing networks within these populations.

THE VARIETY IN SELECTION OF TOPICS FOR NETWORK SCIENCE RESEARCH IN A NATIONAL COLLEGE OF TECHNOLOGY IN JAPAN

Toshihiro Tanizawa

Kochi National College of Technology, Japan

National Colleges of Technology (NCT) in Japan are providing students from 15 to 20 years old with practical knowledge and skills for working as engineers in various industries. As a network scientist in an NCT, I encourage my students to choose topics of their graduation research projects freely from any fields according to their interest. In this talk, I am going to show some unique examples from their research projects, such as "Extracting music theory from network visualization of a musical piece of Beethoven," "Social network analysis of human relationship in Korean independence movement from Japan," "New ranking method in the Robot Competition of National Colleges of Technology," and so on, and see how the network science offers students opportunities to see various things from a new perspective.

A PRE-COLLEGE TRAINING PROGRAM IN NETWORK SCIENCE TECHNIQUES AND THE EFFECTS OF THE MUSIC ON THE BRAIN: A NETSCI ED CASE STUDY PILOT

Robin W. Wilkins¹, Mikayla Slomski² and Michelle Lovett

¹Laboratory for Network Neuroimaging of Complex Systems, Gateway MRI Center, Joint School for Nanoscience and Nanoengineering Gateway Research Park University of North Carolina Greensboro

²Southwest High School, Guilford County Public Schools, High Point, North Carolina

This NetSci Ed pilot project encompasses crosscutting training from three fields: network science, neuroimaging and music. As a pre-college experience, this effort captures a student’s natural scientific curiosity, via their interest in the effects of music on the brain, to learn challenging new knowledge and technically demanding skills. The goals of the

Network Neuroscience project are to encourage and inform students in the techniques of network science through hands-on experiences with neuroimaging data. Participants in the project have a background and interest in both music and science. Students finish the program having acquired an understanding of the basics of network science, functional magnetic resonance imaging (fMRI), the application of network science techniques to large neuroimaging data sets, and the effects of music on the brain. As a senior research project, a scientific paper and presentation by the student concludes the program. The potential from this type of interest-driven, high school level experience may translate to a variety of future 21st century data-driven career possibilities. Future directions, including the potential arising from this interdisciplinary field, are discussed.

TOWARD AN INTERSCALE NETWORK MODEL OF LEARNING

Stephen M. Uzzo

New York Hall of Science

There is tremendous interest in functionally and structurally modeling the brain, its evolution and dynamics. Three significant initiatives are underway to accomplish this, including the Human Connectome Project, The Blue Brain, and the BRAIN initiative. What all of these projects have in common is that they look for functional and structural connections within the brain and try to map them. But when we look at the process of learning from a network perspective, we realize that the physical brain is just a part of the equation. Recent research into brain function and theories about embodied cognition point to the need to map whole dynamic neurological systems, their environmental contexts and interscale behaviors in order to understand the process of learning in any meaningful way. This will be needed to revise cognitive and learning sciences, and ultimately, teaching and learning practice. This talk will describe what is missing in the study of learning and the network basis for a new human learning model.

ENGAGING HIGH SCHOOL CURRICULA VIA NETWORK SCIENCE - LESSONS LEARNED FROM WORKING WITH TEACHERS

Lori Sheetz, USMA West Point

Components of networks and network thinking have been used as a tool for teaching math, computer science, and technology in informal education settings for over 20 years. More recently network scientists have expanded these efforts by developing and sharing informal outreach materials which demonstrate how network science can successfully be used to engage students in STEM fields, to learn problem solving skills, and to begin building

interdisciplinary habits of mind. These successes led to the idea that network science could be used as a tool within formal education venues. In this talk I will share lessons learned from working with teachers as we begin to shift network science from an informal science research tool to a blended formal/informal education model. I will discuss teacher concerns and barriers to learning that we have worked through and some that we are still struggling to resolve. This will set the stage for some of the collaborative work participants at NetSci Ed3 will assist with as the research community begins to build a framework for network science literacy standards.

NETLOGO LATEST RELEASE: NEW NETWORKS-EXTENSION

Arthur Hjorth, Northwestern University

We are happy and proud to present the latest release of NetLogo which includes the new Networks-extension. NetLogo is one the most widely used Agent-based Modeling languages in education and research, and with its latest release, its capacities for (social) networks science and analysis take a quantum leap. In this talk, we present the new Networks-extension, and its features. In short, the Networks-extension allows users to easily build or import network data, and use NetLogo's low-threshold syntax to dynamically and programmatically manipulate them. This allows learners and designers of learning environments to build learning activities that align with learning design principles identified in Learning Sciences research. Finally, we present some examples of how we have already used it to design engaging learning activities that draw both implicitly and explicitly on networks science principles.