Computational Thinking Integration into Middle Grades Science Classrooms: Strategies for Meeting the Challenges

This paper reports findings from the efforts of a university-based research team as they worked with middle school educators within formal school structures to infuse computer science principles and computational thinking practices. Despite the need to integrate these skills within regular classroom practices to allow all students the opportunity to learn these essential 21st Century skills, prior practice has been to offer these learning experiences outside of mainstream curricula where only a subset of students have access. We have sought to leverage elements of the research-practice partnership framework to achieve our project objectives of integrating computer science and computational thinking within middle science classrooms. Utilizing a qualitative approach to inquiry, we present narratives from three case schools, report on themes across work sites, and share recommendations to guide other practitioners and researchers who are looking to engage in technology-related initiatives to impact the lives of middle grades students

Skills and Knowledge for Data-Intensive Environmental Research.

The scale and magnitude of complex and pressing environmental issues lend urgency to the need for integrative and reproducible analysis and synthesis, facilitated by data-intensive research approaches. However, the recent pace of technological change has been such that appropriate skills to accomplish data-intensive research are lacking among environmental scientists, who more than ever need greater access to training and mentorship in computational skills. Here, we provide a roadmap for raising data competencies of current and next-generation environmental researchers by describing the concepts and skills needed for effectively engaging with the heterogeneous, distributed, and rapidly growing volumes of available data. We articulate five key skills: (1) data management and processing, (2) analysis, (3) software skills for science, (4) visualization, and (5) communication methods for collaboration and dissemination. We provide an overview of the current suite of training initiatives available to environmental scientists and models for closing the skill-transfer gap

Introducing Preservice STEM Teachers to Computer Science: A Narrative of Theoretically Oriented Design

This paper narrates the process of designing a curricular unit that serves to introduce preservice science, technology, engineering, and mathematics (STEM) teachers to computer science (CS) education. Unlike most literature that focuses on results and findings, this paper explains how a justice-centered approach to CS education informed decisions about the theoretical underpinnings of curricular design choices. Situated in issues related to the gentrification of Austin, Texas, the described curricular unit explores how the increased use of CS and growth of the technology sector are having a direct impact on the historically marginalized residents of East Austin. Connected by a theme that maps are both a form of data visualization and political artifact, the described curricular unit uses CS as a tool to: critique the macro-ethics of politics and society; provide a CS learning environment that can be responsive to the multiple social identities of students; and connect CS to larger struggles for justice and liberation.Educatio

Analysis and Perspective from the Complex Aerospace Systems Exchange (CASE) 2013

NASA Langley Research Center embedded four rapporteurs at the Complex Aerospace Systems Exchange (CASE) held in August 2013 with the objective to capture the essence of the conference presentations and discussions. CASE was established to provide a discussion forum among chief engineers, program managers, and systems engineers on challenges in the engineering of complex aerospace systems. The meeting consists of invited presentations and panels from industry, academia, and government followed by discussions among attendees. This report presents the major and reoccurring themes captured throughout the meeting and provides analysis and insights to further the CASE mission

Summary of the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1)

Challenges related to development, deployment, and maintenance of reusable software for science are becoming a growing concern. Many scientists’ research increasingly depends on the quality and availability of software upon which their works are built. To highlight some of these issues and share experiences, the First Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE1) was held in November 2013 in conjunction with the SC13 Conference. The workshop featured keynote presentations and a large number (54) of solicited extended abstracts that were grouped into three themes and presented via panels. A set of collaborative notes of the presentations and discussion was taken during the workshop. Unique perspectives were captured about issues such as comprehensive documentation, development and deployment practices, software licenses and career paths for developers. Attribution systems that account for evidence of software contribution and impact were also discussed. These include mechanisms such as Digital Object Identifiers, publication of “software papers”, and the use of online systems, for example source code repositories like GitHub. This paper summarizes the issues and shared experiences that were discussed, including cross-cutting issues and use cases. It joins a nascent literature seeking to understand what drives software work in science, and how it is impacted by the reward systems of science. These incentives can determine the extent to which developers are motivated to build software for the long-term, for the use of others, and whether to work collaboratively or separately. It also explores community building, leadership, and dynamics in relation to successful scientific software

Model Reduction of Synchronized Lur'e Networks

In this talk, we investigate a model order reduction schemethat reduces the complexity of uncertain dynamical networks consisting of diffusively interconnected nonlinearLure subsystems. We aim to reduce the dimension ofeach subsystem and meanwhile preserve the synchronization property of the overall network. Using the upperbound of the Laplacian spectral radius, we first characterize the robust synchronization of the Lure network bya linear matrix equation (LMI), whose solutions can betreated as generalized Gramians of each subsystem, andthus the balanced truncation can be performed on the linear component of each Lure subsystem. As a result, thedimension of the each subsystem is reduced, and the dynamics of the network is simplified. It is verified that, withthe same communication topology, the resulting reducednetwork system is still robustly synchronized, and the apriori bound on the approximation error is guaranteed tocompare the behaviors of the full-order and reduced-orderLure subsyste