2026 ASEE Annual Conference & Exposition

Towards a Metasynthesis of Recent K-12 Computer Science Education Research (Fundamental)

Presented at Pre-College Engineering Education Division (PCEE) Technical Session 6

Introduction. This fundamental research paper explores dimensions of a metasynthesis of K-12 computer science (CS) education research. In recent years, the study of K-12 CS education has grown in breadth and depth across various topics and contexts. Individual literature reviews can cover a topic or a context, but it is challenging to answer more comprehensive questions, like What teaching strategies works best for various populations and classroom contexts? Such a question requires a broader view of the corpus of literature.

Research Objective. This paper describes part of a pilot project designed to create a tool-supported, human-produced synthesis of recent K-12 CS education research. Our research question addressed in this paper was: What does the set of human extracted, cleaned and organized findings reveal about the state of K-12 CS education research?

Methodology and Processes. After establishing an inclusion/exclusion criteria of papers that focus on the student impacts of CS education, we then identified over 300 studies published from 2021 to mid-2024. We categorized study findings according to the extended CAPE framework, which is a taxonomy of factors related to capacity, access, participation, and experience in CS and extracted interventions and findings.

Results. Curricula designed to teach computational thinking (CT) are exceptionally common, while research on appropriate hardware for teaching computer science is quite uncommon. Similarly, affective outcomes (e.g., attitude toward CS) are often part of a study’s outcomes, while social-familial influences are much less likely to be explored. Research that explores content knowledge frequently focuses on topics related to algorithms and programming and rarely focuses on social and cultural impacts of computing.

Implications. As a result of this analysis, we are able to provide computer science education researchers with both an overview of the landscape of existing research as well as indicators of underexplored topics that would benefit from additional research.

How AI Was Used. AI was used to support creating code for data analysis and for data visualization.

Authors

Dr. Julie M. Smith http://orcid.org/0000-0003-2347-2070 Institute for Advancing Computing Education [biography]

Dr. Julie M. Smith is a senior education researcher at the Institute for Advancing Computing Education. She holds degrees in Software Development, Curriculum & Instruction, and Learning Technologies. Her research focus is computer science education and AI education, particularly the intersection of learning analytics, learning theory, and broadening participation. She was a research assistant at MIT’s Teaching Systems Lab; she is also co-editor of the SIGCSE Bulletin.
Monica McGill http://orcid.org/0000-0002-3096-9619 Institute for Advancing Computing Education [biography]

Monica McGill is President & CEO of the Institute for Advancing Computing Education (formerly known as CSEdResearch.org). Have previously worked in industry and academia, McGill is using her experiences as a computer scientist, professor, and researcher to enable others to build a strong foundation of CS education research focused on all children while also honoring their backgrounds and experiences.
Mr. Precious Chukwuweike Eze http://orcid.org/0000-0001-5324-5018 Florida International University [biography]

Precious Eze is a first-year doctoral student in Engineering and Computing Education at SUCCEED, Florida International University, and advised by Dr. Bruk Berhane. Before Coming to FIU, he completed his undergraduate degree in Chemical Engineering ( 2008 - 2012) at Enugu State University, Nigeria, and his Master’s degree in Chemical Engineering (Cum Laude ) from 2017-2019 at the University of South Africa. He has also taught Physics & Engineering Sciences at High School, and College Levels in South Africa from 2014 - to 2017 and was a graduate research assistant at the University of South Africa from 2018 - to 2020. Eze is also a member of the Engineering Council of South Africa, IBM South Africa Data Science Group, and the Engineering Education African Fellows. His research interest is in Technology Enhanced Learning, specifically: “Examining the potential of AI to improve learning in Engineering & Computing Education in line with the sustainable development goals and UNESCO 2030 agenda.”
Charity Oluwafunmbi Odetola [biography]

Charity Oluwafunmbi Odetola is a graduate student at the University of North Carolina Greensboro (UNCG), where she is pursuing a doctorate in Educational Research Methodology (ERM), with an emphasis on Program Evaluation. She is an emerging evaluator and dedicated researcher whose work focuses on decolonizing methodologies in both research and evaluation theory and practice. While her primary academic focus centers on the African diaspora and evaluation, her broader research spans STEM and social justice-oriented research.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 21, 2026, and to all visitors after the conference ends on June 24, 2026

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