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Wyoming recently mandated that computer science instruction be provided in K-12 schools by 2022, and there is an urgent need for designing instruction that can integrate computer science into the teaching of other subjects. This project assembles a network improvement community comprised of partners from the University of Wyoming, community colleges, Wyoming school districts, the Wyoming Library System, the Wyoming Department of Education, and local software development firms. The community meets once monthly over the duration of the project to collaborate stakeholder agendas for meeting the project goals. The community enlists K-8 teachers from across the state to experience professional development and collaborate on integrating computer science into their instruction of STEM and social science topics. The project is producing units for teachers, who are implementing these units with support from master teachers and educational scholars. The community serves as a forum for teachers to debrief and learn from each other about ways to improve their instruction and design of the curricular units. Libraries in the state system act as partners for dissemination to rural areas of the innovative instructional approaches. WySLICE prepares 150 K-8 teachers and state librarians from all disciplines to integrate computer science into their teaching. The project is reaching almost half of all K-8 students in Wyoming. The research questions address how teachers use modeling practices as supports for student understanding of algorithms and coding in a variety of ways. The curricula involve cybersecurity as well as other topics relevant to measurement in mathematics and social studies topics that involve social concerns like voting. Data sources include teacher lesson plans and recordings of their instructional implementation, scoring of each of these according to a rubric, meeting notes of monthly meetings, and results from pre-post student assessments. The evaluation focuses on the meeting of project goals and the quality of the management of the network improvement community. This project is jointly funded by CS for All and the Established Program to Stimulate Competitive Research (EPSCoR). This work is supported by the National Science Foundation under DRL Grant #1923542 "CS For All:RPP - Booting Up Computer Science in Wyoming." 

The current state of computer science education has garnered concern across the world as the demand for computer science literacy has grown in professional careers. Computer science is integral to problem solving across the STEM field. Motivated by the need to teach students crucial computer science skills, outreach camps were held for middle and high school students and specifically focused on cybersecurity. This research focused on two main questions: 1. How do week-long outreach activities impact student interest in cybersecurity? 2. How do these activities influence student behavior online? 

Groundwater discharge though streambeds is often focused toward discrete zones, indicating that preliminary reconnaissance may be useful for capturing the full spectrum of groundwater discharge rates using point-scale quantitative methods. However, many direct-contact reconnaissance techniques can be time-consuming, and remote sensing (e.g., thermal infrared) typically does not penetrate the water column to locate submerged seepages. In this study, we tested whether dozens of groundwater discharge measurements made at “uninformed” (i.e., selected without knowledge on high-resolution temperature variations at the streambed) point locations along a reach would yield significantly different Darcy-based groundwater discharge rates when compared with “informed” measurements, focused at streambed thermal anomalies that were identified a priori using fiber-optic distributed temperature sensing (FO-DTS). A non-parametric U-test showed a significant difference between median discharge rates for uninformed (0.05 m·day−1; n = 30) and informed (0.17 m·day−1; n = 20) measurement locations. Mean values followed a similar pattern (0.12 versus 0.27 m·day−1), and frequency distributions for uninformed and informed measurements were also significantly different based on a Kolmogorov–Smirnov test. Results suggest that even using a quick “snapshot-in-time” field analysis of FO-DTS data can be useful in streambeds with groundwater discharge rates <0.2 m·day−1, a lower threshold than proposed in a previous study. Collectively, study results highlight that FO-DTS is a powerful technique for identifying higher-discharge zones in streambeds, but the pros and cons of informed and uninformed sampling depend in part on groundwater/surface water exchange study goals. For example, studies focused on measuring representative groundwater and solute fluxes may be biased if high-discharge locations are preferentially sampled. However, identification of high-discharge locations may complement more randomized sampling plans and lead to improvements in interpolating streambed fluxes and upscaling point measurements to the stream reach scale.