Barriers to accessing computing

The crux of my dissertation work is exploring the supports and barriers to accessing computing at the school level. I explore the relationship between public high schools in Georgia offering computer science and possible predictive variables at the school, district, and county levels. I follow this with building case studies of select schools that personify different aspects of the computer science landscape, to investigate esoteric variables that aren’t currently gathered in large, publicly-available data sets.


Parker, M. C., & Guzdial, M. (2019, July). A Statewide Quantitative Analysis of Computer Science: What Predicts CS in Georgia Public High School?. In Proceedings of the 2019 ACM Conference on International Computing Education Research (pp. 317-317). ACM.

influences to success in computing

Socioeconomic status (SES) is correlated with academic achievement, including computer science achievement. We explored the relationship between SES and CS achievement via mediating variables, namely spatial reasoning and access to computing. We found further evidence to support the relationship between spatial reasoning and SES and CS, which is promising for future efforts to minimize achievement gaps for low-SES students in CS.


Parker, M. C., Solomon, A., Pritchett, B., Illingworth, D. A., Marguilieux, L. E., & Guzdial, M. (2018, August). Socioeconomic Status and Computer Science Achievement: Spatial Ability as a Mediating Variable in a Novel Model of Understanding. In Proceedings of the 2018 ACM Conference on International Computing Education Research (pp. 97-105). ACM.

measuring success in computing

The Second CS1 Assessment (SCS1) is a validated, pseudocode-based assessment for introductory computing. We share our process of replicating a previously validated assessment and validating the replication. The SCS1 can be used to measure student learning in various research interventions and to build and improve other CS assessments.

If you’re interested in using the SCS1 in your classroom or research, please click here for more information.


Parker, M. C., Guzdial, M., & Engleman, S. (2016, August). Replication, validation, and use of a language independent CS1 knowledge assessment. In Proceedings of the 2016 ACM conference on international computing education research (pp. 93-101). ACM.

As computer science grows, teachers need resources for learning the content and pedagogical content knowledge needed to teach their students. Our work has focused on building browser-based eBooks for computer science, especially for AP CS Principles. Even though both teacher and students are learning the material for the first time, our research provides evidence that teachers use the eBook differently than their students.

Check out our eBook for students in CS Principles here.


Ericson, B. J., Rogers, K., Parker, M., Morrison, B., & Guzdial, M. (2016, August). Identifying design principles for CS teacher Ebooks through design-based research. In Proceedings of the 2016 ACM Conference on International Computing Education Research (pp. 191-200). ACM.

Parker, M. C., Rogers, K., Ericson, B. J., & Guzdial, M. (2017, August). Students and Teachers Use An Online AP CS Principles EBook Differently: Teacher Behavior Consistent with Expert Learners. In Proceedings of the 2017 ACM Conference on International Computing Education Research (pp. 101-109). ACM.

Tools for Learning CS

Understanding Runtime Analysis

Big-O analysis can be an incredibly difficult topic for undergraduates learning computer science. What is it about runtime analysis that make it hard for students to understand? We found that logarithms are a critical piece of the puzzle.


Parker, M., & Lewis, C. (2014). What makes big-O analysis difficult: understanding how students understand runtime analysis. Journal of Computing Sciences in Colleges, 29(4), 164-174.