Academic Research Reports

Thompson, A. (2021). Investigating Inequities in Disciplianary Actions within Shelby County Schools.

Black students, and Black males specifically, have been shown to have substantially higher rates of office disciplinary referrals (ODRs) and exclusionary ODRs than their White and Latinx peers. The current study explored the student (race, gender, poverty status) and school-level variables (grade-level served, enrollment size, student body composition, and teacher demographics) that contributed to these disparities. The results of the OLS multiple regression revealed that although Black students and Black male students were referred to the office and excluded from school at higher rates than their counterparts in middle and high school, greater disparities existed between Black male students and White male and female students and between Black male students and Latina students in elementary schools. In elementary school, the percentages of White teachers in schools predicted disparities between Black males and White females and between Black males and Latinas. Other student-level predictors included the concentrations of Black students in elementary and high school and the concentrations of poor students in middle and high school.

Thompson, A. (2018, May). The Academic Outcome of Students Affected by School Closures

District Superintendents and school board members decide to close schools for several reasons, including declining enrollment, deteriorating facilities, and low academic achievement. Parents, students, teachers, and district leadership are not only concerned about the effect these closures have on the students being displaced, but also on those attending the schools into which these students will be integrating. Therefore, this study sought to determine whether school closures had any impact on the academic achievement of either student body. The outcome variable was students’ proficiency level on the Reading/Language Arts and/or Mathematics section of the statewide standardized achievement test. The results of the analysis allowed district leaders to action plan, identifying areas of strength as well as growth opportunities, to improve academic and behavioral outcomes for all students.

Thompson, A. (2017). The Effectiveness of Early Warning Indicators (EWI) in Dropout Prevention.

Early Warning Indicators (EWIs) are markers that identify students who are moving towards thresholds of performance indicating they are off track for graduating on time. While the specific benchmarks for these indicators can vary across school districts, they usually include attendance, behavior, and course performance. This study examined the 2016 cohort of middle school students to determine which factors were most predictive of dropping out of high school. Controlling for other variables in the model, males, and students who were economically disadvantaged and overage for grade were more likely to drop out. Other factors that increased the likelihood of dropping out were chronic absenteeism, failing two or more courses over their cumulative time in middle school, being suspended or expelled four or more times during middle school, and being out of school for three or more days between enrollments. Findings from this research project allowed district decision-makers to implement targeted strategies and interventions to improve on-time graduation rates.

Conference Publications

Thompson, A. (2023, March). Building Capacity among Black CS Educators (Moderator for panel discussion).

SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education. K-12: Curricula & Teacher Programs.

What support do Black Computer Science (CS) educators need to succeed? In this panel, Black CS teachers shared their perspectives on what is needed to encourage Black teachers to teach CS. We also discussed barriers to participation and what Black CS teachers need to feel supported and included in a field where they are severely underrepresented.

McGill, M.; Thompson, A.; Gransbury, I.; Heckman, S.; Rosato, J.; Delyser, L. A. (2023, March). Building upon the CAPE Framework for Broader Understanding of Capacity in K-12 CS Education.

SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education.

The CAPE Framework has been used in multiple studies to situate capacity-building efforts within schools to offer equitable student access to and participation in K-12 computer science (CS) education. CAPE defines four major components of capacity, access, participation, and experience. However, to define what each of the CAPE components can entail, well-defined subcomponents are needed. We conducted a qualitative content analysis by creating a codebook from an existing data framework and literature review. We reframed earlier findings on factors that influence student learning and academic achievement into the CAPE. We vetted an expanded framework that includes eight Capacity subcomponents, a third (categories) layer, and a fourth (subcategories) layer that can be used to disaggregate the many elements that comprise Capacity. For our trial analysis of 196 articles, we added several codes at the category and subcategory level but found no gaps in the codes for our a priori defined subcomponents.

McGill, M.; Thompson, A.; Snow, E.; DeLyser, L. A.; Wortel-London, S.; Vaval, L. (2022, June). Comparing Access and Participation Outcomes of Schools Engaged in a Multi-school CS and Cybersecurity Intervention (Evaluation).

SIGCSE 2023: Proceedings of the 54th ACM Technical Symposium on Computer Science Education.

ASEE 2022 Annual Conference & Exposition. Pre-College Engineering Education Technical Session 7: Cybersecurity & Computing.

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 of the intervention’s impacts, we turned our attention to whether or not the outcomes were influenced by the 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.

ASEE 2022 Annual Conference & Exposition. Pre-College Engineering Education Technical Session 7: Cybersecurity & Computing.

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 [1]. 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 number 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 in using technology, improved overall; however, students interested in taking additional CS courses were significantly lower in schools primarily serving historically underrepresented students. Last, the number of students taking the AP CS A and AP CS Principles exams declined overall.