The process of increasing student exposure to computational thinking in K-12 is complex, requiring systemic change, teacher engagement, and development of signifi cant resources. Collaboration with the computer science education community is vital to this effort.

The biotic resistance hypothesis predicts that diverse native communities are more resistant to invasion. However, past studies vary in their support for this hypothesis due to an apparent contradiction between experimental studies, which support biotic resistance, and observational studies, which find that native and non-native species richness are positively related at broad scales (small-scale studies are more variable). Here, we present a novel analysis of the biotic resistance hypothesis using 24 456 observations of plant richness spanning four community types and seven ecoregions of the United States. Non-native plant occurrence was negatively related to native plant richness across all community types and ecoregions, although the strength of biotic resistance varied across different ecological, anthropogenic and climatic contexts. Our results strongly support the biotic resistance hypothesis, thus reconciling differences between experimental and observational studies and providing evidence for the shared benefits between invasive species management and native biodiversity conservation.

PANEL SUMMARYThe number of undergraduates entering computer science has declined in recent years. This is paralleled by a drop in the number of high school students taking the CS AP exam and the number of high schools offering computer science courses. The declines come at a time when career opportunities in CS continue to grow and computer science graduates are seen as crucial in building a globally competitive workforce for the 21 st century. Efforts aimed at reversing the declining interest in computer science include curriculum revisions at the undergraduate level at many institutions, a re-design of computer science AP courses [1], and the inclusion of computational thinking into disciplines outside computer science [3].This panel discusses four projects of computer science researchers collaborating with high school teachers on integrating computing and computational thinking into their courses. The majority of the high school teachers involved is teaching science and math courses. They are teaching a diverse group of talented and college-bound students. The goal of all projects is to integrate computing into disciplines represented in the high school curriculum and to raise the awareness of computer science as an exciting and intellectually rewarding field. This panel will outline recent and on-going activities and interaction with high school teachers. Each panelist will describe how he/she got involved and the nature of the interaction. The panelists will talk about their individual projects, outline their visions for future interactions, and how their effort can be replicated by others. The session will briefly describe NSF's RET program which provided teacher support for three of the four projects. The session will then be opened for discussion; the audience will be encouraged to ask questions and contribute additional ideas for the inclusion of computational thinking in high school courses.The "Science Education in Computational Thinking (SECANT)'' project at Purdue University collaborated with two high school physics teachers to incorporate selected material of the Matter&Interaction (M&I) Curriculum with computational thinking principles into high school physics courses [3]. The high school course includes three weeks of Python programming focusing on computational methods and visualizations crucial to the M&I Curriculum. Lab material developed within this project gives a first introduction to programming. Throughout the school year, students use computation to illustrate and simulate physical principles and models, and they apply computational thinking concepts. The computational concepts include designing repeated processes through iterations, determining how data generated is stored and represented, abstracting and generalizing physical processes, and visualizing the collected data to observe patterns and other phenomena.This approach is currently implemented in the AP Physics course. The high school devotes a full year to AP Physics and has some flexibility on what material to cover. Introducing ...

No abstract

No abstract