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Problem. Extant measures of students’ cybersecurity self-efficacy lack sufficient evidence of validity based on internal structure. Such evidence of validity is needed to enhance confidence in conclusions drawn from use of self-efficacy measures in the cybersecurity domain. Research Question. To address this identified problem, we sought to answer our research question: What is the underlying factor structure of a new self-efficacy for Information Security measure? Method. We leveraged exploratory factor analysis (EFA) to deter- mine the number of factors underlying a new measure of student self-efficacy to conduct information security. This measure was created to align with the five elements of the information security section of the K-12 Cybersecurity Education framework. Participants were 190 undergraduate students recruited from computer science courses across the U.S. Findings. Results from the EFA indicated that a four-factor solution best fit the data while maximizing interpretability of the factors. The internal reliability of the measure was quite strong (𝛼 = .99). Implications. The psychometric quality of this measure was demonstrated, and thus evidence of validity based on internal structure has been established. Future work will conduct a confirmatory factor analysis (CFA) and assess measurement invariance across sub- groups of interest (e.g., over- vs. under-represented race/ethnicity groups, gender). 

Research Problem: K-12 school systems are racing to implement Computer Science (CS) education within classrooms across the United States. Prior research on education reform movements suggests that without rigorous research, combined with careful technical support for implementation, we should expect wide variation across districts in how they choose to implement computer science education as well as extreme inequality in which districts provide equitable opportunities to learn CS, with the most underserved students fairing the worst (Ahn & Quarles, 2016; Bryk, Gomez, Grunow, & LeMahieu, 2015; Carlson, Borman, & Robinson, 2011; Gordon and Heck, 2019). It stands to reason that these same challenges are at play in the CS subfield of cybersecurity. Research Question: In what ways does the JROTC-CS experience impact the cognitive (e.g. knowledge and skills) and non-cognitive factors (e.g. social and emotional behaviors) of cadets in high school? Methodology: We used a qualitative study using a semi-structured interview protocol with JROTC cadets attending the schools involved in the intervention (n=17). The interview protocol focused on the types of cognitive and non-cognitive impacts the cadets experienced when participating in CS and Cybersecurity learning experiences. Data Collection: We conducted interviews with 17 cadets and coded the transcripts using a priori codes. Findings: Sixteen of the students reported an increase in their knowledge and skills through self-reported grades and self-perceived knowledge gained through the CS and cybersecurity experiences. While all of the students indicated that the courses and extracurricular activities were beneficial and interesting, only two of the students indicated they wanted to have a career in the computer science or cybersecurity field. However, the findings indicated a lack of school personnel support, specifically at the guidance counselor level. Finally, all of the students reported a strong sense of belonging in their CS and cybersecurity experiences leading to increased peer collaboration and support. Implications: Based on other evidence collected during the intervention, the intervention had multiple successes in expanding equitable experiences for cadets in the schools involved in the study. Guidance counselors and other personnel who are in a position to influence the future career choices of cadets may need more professional development; however, more research is needed to understand the ways in which they currently influence cadets. 

With more recognition being given to the diverse and changing demographics in education, there is a need to understand how well computer science education is meeting the needs of all learners as it starts to infiltrate K-12 schools. The CAPE framework is a newer model for assessing the equitable delivery of computer science education and can be used to understand a school’s capacity to offer equitable computer science (CS) education, equitable student access to CS education, equitable student participation in CS, and equitable experiences of students taking CS. Since the CAPE framework is a new way to research CS education through an equity-lens, there are few, if any, frameworks that can be leveraged to explore research questions in a complex, multi-school intervention. To address this gap, we used a design-based research approach to create and determine the feasibility of a new model, Theory of Impacts, informed by the CAPE framework (the ToI-CAPE model), for evaluating a multi-school intervention. In this article, we provide a detailed explanation of creating and using the ToI-CAPE model for a specific intervention and the feasibility of using ToI-CAPE across factors based in experiences and how to use this model in other research and evaluation projects. Overall, the use of the ToI-CAPE model can be used to shed light on the critical subcomponents and agents at work in the intervention and the actions necessary across these components and agents to support intended outcomes. 

Research Problem. Computer science (CS) education researchers conducting studies that target high school students have likely seen their studies impacted by COVID-19. Interpreting research findings impacted by COVID-19 presents unique challenges that will require a deeper understanding as to how the pandemic has affected underserved and underrepresented students studying or unable to study computing. Research Question. Our research question for this study was: In what ways has the high school computer science educational ecosystem for students been impacted by COVID-19, particularly when comparing schools based on relative socioeconomic status of a majority of students? Methodology. We used an exploratory sequential mixed methods study to understand the types of impacts high school CS educators have seen in their practice over the past year using the CAPE theoretical dissaggregation framework to measure schools’ Capacity to offer CS, student Access to CS education, student Participation in CS, and Experiences of students taking CS. Data Collection Procedure. We developed an instrument to collect qualitative data from open-ended questions, then collected data from CS high school educators (n = 21) and coded them across CAPE. We used the codes to create a quantitative instrument. We collected data from a wider set of CS high school educators ( n = 185), analyzed the data, and considered how these findings shape research conducted over the last year. Findings. Overall, practitioner perspectives revealed that capacity for CS Funding, Policy & Curriculum in both types of schools grew during the pandemic, while the capacity to offer physical and human resources decreased. While access to extracurricular activities decreased, there was still a significant increase in the number of CS courses offered. Fewer girls took CS courses and attendance decreased. Student learning and engagement in CS courses were significantly impacted, while other noncognitive factors like interest in CS and relevance of technology saw increases. Practitioner perspectives also indicated that schools serving students from lower-income families had 1) a greater decrease in the number of students who received information about CS/CTE pathways; 2) a greater decrease in the number of girls enrolled in CS classes; 3) a greater decrease in the number of students receiving college credit for dual-credit CS courses; 4) a greater decrease in student attendance; and 5) a greater decrease in the number of students interested in taking additional CS courses. On the flip-side, schools serving students from higher income families had significantly higher increases in the number of students interested in taking additional CS courses. 

In early 2020, a cohort of 30 high schools engaged in a year-long intervention designed to increase their ability to offer Computer Science (CS) and Cybersecurity education to their students. After we performed an evaluation on the intervention’s impacts, we turned our attention to whether or not the outcomes were influenced by engagement of the schools in the cohort. In this research paper, we focus on the guiding research question: How do schools’ engagement in an intervention designed to build equitable CS and Cybersecurity education capacity impact schools’ course offerings and students’ participation in these courses? To measure equitable impact, we evaluated changes to actual CS and Cybersecurity course offerings and enrollment at the schools. We focused on the differences in participation across student gender and race/ethnicity as well as participation levels at the different schools across three years prior to the intervention and one year after the intervention. Findings indicate that, despite the disruption to schools from the COVID-19 pandemic, schools engaged in the program had very significant increases in AP CSP, AP CS A, and Cybersecurity course offerings and enrollment, particularly at schools that serve students from low-income families. 

Practitioners delivering computer science (CS) education during the COVID-19 pandemic have faced numerous challenges, including the move to online learning. Understanding the impact on students, particularly students from historically marginalized groups within the United States, requires deeper exploration. Our research question for this study was: \textit{In what ways has the high school computer science educational ecosystem for students been impacted by COVID-19, particularly when comparing schools that have student populations with a majority of historically underrepresented students to those that do not?} To answer this question, we used the CAPE theoretical framework to measure schools’ Capacity to offer CS, student Access to CS education, student Participation in CS, and Experiences of students taking CS \cite{fletcherwarner2021cape}. We developed a quantitative instrument based on the results of a qualitative inquiry, then used the instrument to collect data from CS high school practitioners located in the United States (n=185) and performed a comparative analysis of the results. We found that the numbers of students participating in AP CS A courses, CS related as well as non-CS related extracurricular activities, and multiple extracurricular activities increased. However, schools primarily serving historically underrepresented students had significantly fewer students taking additional CS courses and fewer students participating in CS related extracurricular activities. Student learning in CS courses decreased significantly; however, engagement did not suffer. Other noncognitive factors, like students’ understanding of the relevance of technology and confidence using technology, improved overall; however, student interested in taking additional CS courses was significantly lower in schools primarily serving historically underrepresented students. Last, the numbers of students taking the AP CS A and AP CS Principles exams declined overall. 

Practitioners delivering computer science (CS) education during the COVID-19 pandemic have faced numerous challenges, including the move to online learning. Understanding the impact on students, particularly students from historically marginalized groups within the United States, requires deeper exploration. Our research question for this study was: In what ways has the high school computer science educational ecosystem for students been impacted by COVID-19, particularly when comparing schools that have student populations with a majority of historically underrepresented students to those that do not? To answer this question, we used the CAPE theoretical framework to measure schools’ Capacity to offer CS, student Access to CS education, student Participation in CS, and Experiences of students taking CS. We developed a quantitative instrument based on the results of a qualitative inquiry, then used the instrument to collect data from CS high school practitioners located in the United States (n=185) and performed a comparative analysis of the results. We found that the numbers of students participating in AP CS A courses, CS related as well as non-CS related extracurricular activities, and multiple extracurricular activities increased. However, schools primarily serving historically underrepresented students had significantly fewer students taking additional CS courses and fewer students participating in CS related extracurricular activities. Student learning in CS courses decreased significantly; however, engagement did not suffer. Other noncognitive factors, like students’ understanding of the relevance of technology and confidence using technology, improved overall; however, student interested in taking additional CS courses was significantly lower in schools primarily serving historically underrepresented students. Last, the numbers of students taking the AP CS A and AP CS Principles exams declined overall.