Embracing the idea that all students should learn the fundamentals of computer science (CS), the United States has funded the development of coalitions designed to expand CS education. This poster employs an exploratory comparative analysis using simple descriptive statistics to examine potential impacts of broadening participation in computing (BPC) coalitions, focusing specifically on measurement of the Expanding Computing Education Pathways (ECEP) Alliance in relation to state-level CS course access, state-level CS course participation, and states' adoption of the Code.org Advocacy Coalition's 10 Policies. Findings include that ECEP states consistently demonstrated higher rates of CS course access and participation than non-ECEP states. ECEP states also were either at parity or above in their adoption of CS education policies. In the live poster discussion, we will theorize these differences might be linked to the elements of the ECEP Model of State Change. Given the ongoing investment in BPC coalitions, these initial findings indicate promising results and warrant further research.

Are you looking to learn more about developing and executing research plans to best meet the needs of your CS education projects? Utilizing case studies from the evaluation research group at the Texas Advanced Computing Center intermixed with hands-on activities, this workshop will help you along your research or program evaluation journey! As a workshop participant, you will work through guided practice activities in small groups to deepen your understanding of how to design research and evaluation methods for your program. Key takeaways from this tutorial will be the steps and considerations for developing a research or evaluation plan that aligns data collection activities and analysis to your research or evaluation questions. Instrumentation will also be shared throughout, with participants taking away examples of surveys and interview protocols that have been effectively used by the team at the Texas Advanced Computing Center. Resources will also be provided on how to find additional instruments and how to assess and repurpose those for your projects. This tutorial will help you determine which data is most critical to collect and which methods are best suited for collecting that data based on your participants and program needs and resources.

Physical computing across K-12 and higher education is increasing worldwide. As its popularity grows, the need to generate and leverage high-quality research-based evidence is also increasing. Schools, governments, NGOs, nonprofits and corporations are integrating physical computing for in-school, out-of-school, and employee engagement programs as a result of better access to low cost devices, rising demand for computer science education, updated school curricula, and a shifting global footprint of the semi-conductor industry. While hands-on learning experiences can be some of the most influential in a student's education, they are not guaranteed to lead to positive outcomes. How might we integrate physical computing into existing and new programming to reach students with experiences that positively contribute to their life chances? What are effective strategies for scaling physical computing education programs to ensure the end user - students - are engaging in equitable and culturally relevant/responsive experiences? What key information do decision makers need to consider when organizing, launching, funding and/or assessing such programs? Bring your ideas, questions, stories, and research for discussion with this cross-sector group of physical computing stakeholders.

To understand secondary teachers of computer science's perspectives on barriers to implementing equitable CS instruction during the COVID-19 pandemic, the research team administered a survey to the CS for All Teachers virtual community of practice in Spring 2021 and examined responses from middle and high school teachers of CS (n = 349). We used the CAPE framework (Capacity, Access, Participation, and Experience) to ground our analysis of survey responses. Key Finding 1 is that secondary CS expansion is limited due to competing priorities related to college preparation and standardized testing requirements, which do not usually include CS (Capacity; Access). Key Finding 2 is that student access to broadband at home creates barriers to secondary CS learning (Access; Participation; Experience). These findings reinforce the evidence base that expanding K-12 CS education (before, during, and after COVID-19) faces significant barriers due to gaps and disparities in CS education policies and inequities in students' access to necessary technology.

As access to computer science education at the high school level expands, understanding enrollment in computing courses is vital to ensuring equity of participation. While some countries have made enrollment in computer science coursework in high school compulsory, others have allowed it to be elective. This research tracks a cohort of over 100,000 high school students across a 4-year period with the goal of examining factors related to the odds of enrolling in computer science. These students live in Texas, a state in the United States in which computer science enrollment in high school is optional. Multilevel logistic regression modeling is employed to explore both student-level and school-level factors for students in the cohort to determine the odds of having enrolled in one or more computer science courses throughout the 4-year period. Results of the modeling show significant inequities in enrollment related to gender, race/ethnicity, and socioeconomic status.

Have a CS education research project that needs a survey? If you're an education researcher who wants to learn more about survey instrumentation in order to expedite and improve your research, this session is for you! Come learn how to find, remix, and use existing surveys by delving into the process of taking openly shared resources and repurposing them for your projects. In this workshop, we'll cover basics of survey creation and modification, as well as touch upon some additional useful tips like piloting surveys, how to avoid bots attacking your survey and protecting your participants' privacy. We'll also look at how to choose a survey that fits your needs. You will be actively engaged in hands-on activities. Key takeaways from this workshop will include clear steps you can take to choose an instrument that addresses your research questions and study design, the role that validity and reliability play in instrument design, how to modify an instrument (if needed) to answer your research question, and how to add your instruments to the corpus of instruments at the K-12 CS Education Research Resource Center. Laptop is needed for this workshop.

Collective impact is an approach for solving complex social problems at scale. The challenge of broadening participation in computing (BPC) is one such problem. The complexity of BPC is compounded by the decentralized nature of public education, where decisions are made primarily at the state level and subject to interpretation at the district level. As such, diversifying computer science (CS) pathways across the nation requires a systemic approach such as collective impact to engage all of the stakeholders who influence CS education and whose decisions can either facilitate or hinder BPC efforts. This experience report discusses how the collective impact framework has been used to advance the work of the Expanding Computing Education Pathways (ECEP) Alliance, an NSF funded BPC Alliance focused on states and state policy as the unit of change. We discuss how the five essential features of collective impact (common agenda, shared measurement, mutually reinforcing activities, continuous communication, and backbone support) coalesce to facilitate ECEP's theory of change. The report highlights specific policy changes that ECEP states have addressed to promote BPC, the flipped accountability that results from a non-hierarchical leadership model, and the challenges of measuring systemic changes as an intermediary to BPC.

With the advent of computing education in primary and secondary schools, more research will be needed to determine the best way for students to learn how to think computationally and to design and develop software. As a field, computer science education researchers have been predominantly individuals who are steeped in content knowledge, but often have not had formal training in well-established educational research practices. Likewise, many also focus their research on undergraduate students in their own area of teaching. As the need for research into K-12 computing education grows, so does the opportunity for conducting quantitative studies in the field. In this special session, the presenters will present a broad overview of how to conduct and evaluate quantitative computing education research. The presenters will spend approximately 15 minutes on each of the 4 key areas: designing a study, implementing a study and collecting data, analyzing and interpreting results, and reporting on the study. The remainder of the time will be as a question and answer period with the audience. Since there is considerable overlap between computing education research at the primary/secondary and post-secondary levels, those new to research at the post-secondary level may also benefit from learning about form design, implementation, and reporting of research studies. Key takeaways for this session will include a basic understanding of K-12 computing education research from start to finish as well as a list of well-vetted resources to enable new researchers to explore and learn more.

Developing your computer science education research evaluation instruments from scratch may be no longer necessary thanks to the growing catalog of instruments curated by CSEdResearch.org. This workshop will teach participants how to find, remix, and use existing instruments by delving into the process of taking openly shared resources and repurposing them for your projects. In addition to discussing the importance of using instruments that have been shown to have evidence of reliability and validity, the team from The University of Texas at Austin will discuss how they amended existing surveys and interview protocols to develop tools customized to their needs for their NSF-funded CSforAll Research Practitioner Partnership. Workshop participants will break into groups and be given extensive time to review and revise research instruments. Key takeaways from this workshop will be the steps you need to take to choose an instrument based on your research question and study design, the role that validity and reliability play in instrument design, how to make modifications to an instrument (if needed) to better address your research question, and how to add your instruments to the CSEdResearch.org site.

A complex web of factors can influence whether students participate in computer science (CS) during high school. In order to increase participation in CS for all students, we need to better understand who is currently participating and what factors might be hindering participation. This study utilized a large-scale, student-level dataset from the Texas Education Research Center to investigate factors that predict high school student participation in CS and advanced CS courses. Our dataset contained information on over 1.1 million Texas high school students from the 2017-2018 school year, allowing us visibility into CS course availability in schools, student course taking, and detailed demographic information. We used multilevel mixed-effects logistic regression models to explore predictive factors of student participation in CS and advanced CS courses, limiting our analysis to students whose schools offered CS. In both models, our results showed that students who took Algebra I before high school had more than double the odds of being enrolled in a CS course. This work supports and extends previous understanding of factors that are predictive of CS participation in high school, contributing to the existing literature by uncovering the importance of Algebra I before high school as a potential gatekeeper to participation in CS.

Students living in rural areas are less likely to attend schools that offer computer science (CS) courses largely because educational institutions in these remote areas lack the resources to staff teaching positions for these courses. This study investigated the impact of WeTeach\_CS, a program designed to train teachers to become certified to teach high school CS in Texas. The WeTeach\_CS collective impact model may be well suited to influence rural areas at scale because it utilizes an existing network of organizations across the state to bring high-quality professional development opportunities to teachers in remote areas. Results from a comparative interrupted time series analysis showed a significant, positive change in the rate in which the number of certified CS teachers in rural areas increased during the period of time after WeTeach\_CS began compared to the period before the program was implemented, whereas the number of teachers certified in technology applications showed no such change. Furthermore, the growth rate in the number of certified CS teachers was much higher for rural schools than urban, suggesting that collective impact models like WeTeach\_CS may be especially beneficial for rural communities.