Computational Literacies Lab

Research and Goals

This project has three primary aims, to study the design process and implementation of a CS program, to study and improve computer science pedagogical practices, and to facillitate the creation of a CS teacher residency program. Any attempt at creating such a program will require the support and input of school officials, existing faculty, community members, parents, and (of course) the students themselves (Proctor et. al. 2019).

The research team is studying qualitatively the design process iteself, including the cooperation and negotiation with all interested parties in the design process. Questions about what computer science is, how it should be taught, who should teach it, and what place it has within existing curricular structure are particularly important now, when CS education is poised to become mainstream across New York State and beyond. A successful program is going to require a certain level of support, interest, and even enthusiasm of the community in which it is conceived. To that end, students of the first cohort will be given opportunities to become teachers of adults in their own communitities, teaching the very course they completed. Meanwhile, the undergraduate research assistants will be helping shape and form a new CS teacher residency program at the University at Buffalo, with the nacient CS program serving as a launching pad for future educators.

Summarily, the project has three primary goals:


  1. Study the effectiveness of community involvement in the process of curriculuar design and the formation of positive CS identities among students and community members.
  2. Determine the efficacy of the CS curriculum implemented.
  3. Inform and create an environment for the creation of a CS teacher residency program.

Goal 1: Integrated Community Approach to Curriculum Design

Proctor et. al. (2019) found that various community members had very different opinions, definitions, and priorities when it came to computer science education. Fundamental questions about what computer science and computational thinking are in the first place were by no means clear, and a non-trivial debate persists between CS engineers in the workforce, CS educators, CS education researchers, and the public at large. Since Seymour Papert (1980) first advanced the study of and push for computational thinking in education, theory has come a long way. Wing (2006) defined clearly what is meant by computational thinking and the ways in which it is widely applicable beyond the scope of computer science, and Weintrop's (2016) fleshed out list a clear list of core practices within the scope of computational thinking.

While these definitions and frameworks are naturally useful as a basis for curriculum design, in order for a program to be successful within a specific situated community, feedback from said community is necessary to inform the specifics of the program to ensure continued success, interest, and support in the community. Historically, problems of equity and access have plagued attempts to institute CS curriculum in schools, with a documental lack of CS course offerings in schools with high proportions of students of color (Margolis, Goode, & Chapman, 2015), and while graduation rates of female students in computer science continues to rise, as of 2017 the rate was only 17.9% (Zweben & Bizot 2017). Our research hopes to combat inequity in computer science through the involvement of historically marginalized students and community members in the design of the curriculum itself.

Goals 2: CS Curriculum efficacy

As a template for the curriculum, the research team intends to suggest the Making With Code course, a course that is currently being designed and tested by primary investigator Dr. Chris Proctor and another research team. Unlike many other courses, Making With Code starts students off using the same tools for coding that are generally used by contemporary professional computer scientists, acclimating students to the use of Git Repositories and the use of the command line (terminal), as well as common text editors, with python as the language of choice. The curriculum builds on previous educational coursework and the use of the turtle environment as well as various other libraries. The course incorporates a highly interdisciplinary approach, with geometry, language arts, data science, and even game design. Designed under a project based learning approach, very little time is spent on expository instruction, instead relying on self directed work and one on one feedback by instructors.

Goal 3: CS Teacher Residency Program

The teacher residency paradigm for teacher education has shown considerable promise in recruiting and retaining new teachers, and a large teacher residency program is already well established at the University at Buffalo. Building on the practice of medical residency programs, preservice teachers are paired with highly skilled mentors actively teaching in local schools, and their preparation for teaching takes place less on the college campus, and more in the classroom environments and neighborhoods where those preservice teachers will (hopefully) become employed (Guha et. al. 2017). Computer Science, like any science, requires relatively soteric and deep content knowledge on the part of any would be teacher, in addition to pedagocial content knowledge. While the nature of computer science pedagocial content knowledge is still a matter of highly active research, it is plain that if new CS programs are going to succeed, they will need well trained expert teachers who have both strong CS skills as well as being strong teachers. A part of the design process tasked in this research is the creation of a teacher residency program at the school where undergraduates and graduates can train to become certified CS teachers. Indeed, the existence of partnerships between universities and strong curriculuar programs with expert teachers in local schools is a prerequisite for teacher residency programs, and this research intends to create just such a nascient environment to grow such relationships in the community.


Guha, R., Hyler, M.E., and Darling-Hammond, L. (2016). The Teacher Residency: An Innovative Model for Preparing Teachers. Palo Alto, CA: Learning Policy Institute.

Proctor, Chris, Maxwell Bigman, and Paulo Blikstein. “Defining and Designing Computer Science Education in a K12 Public School District.” In Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 314–20. Minneapolis MN USA: ACM, 2019.

Margolis, J., Goode, J., & Chapman, G. (2015). An equity lens for scaling: A critical juncture for exploring computer science. ACM Inroads, 6(3), 58–66. doi:10.1145/2794294

Weintrop, David, Elham Beheshti, Michael Horn, Kai Orton, Kemi Jona, Laura Trouille, and Uri Wilensky. “Defining Computational Thinking for Mathematics and Science Classrooms.” Journal of Science Education & Technology 25, no. 1 (February 2016): 127–47.

Wing, Jeannette M. “Computational Thinking.” Communications of the ACM 49, no. 3 (March 2006): 33–35.

Zweben, S., & Bizot, B. (2017). 2016 taulbee survey. Computing Research News, 29(5).