A systematic review of “Hour of Code” research

ABSTRACT

Background and Context

Hour of Code is one of the largest educational campaigns implemented. It exposes millions of learners, to an hour of computer science fundamentals. With such a large impact, a large number of research articles have been published on the topic. This research ranges from reports of experiments testing the efficacy of Hour of Code and analysis of learner behavior, to reports of participation and suggestions for facilitating.

Objective

The goal of this work is to determine the effects of Hour of Code on Computer Science education.

Method

Articles in IEEE Xplore, ACM, EBSCO, ERIC, and Google Scholar that include “Hour of Code” were identified. Papers with “Hour of Code” as an emphasis of the research design or exploratory effort were analyzed.

Findings

Systematic review identified 64 papers which were sorted into six categories. Papers focused on overall participation numbers to novel Hour of Code Activities and research using Hour of Code data.

Implications

Analysis of these articles provides detail into the impact of Hour of Code on participants and influences resources for researchers. However, many questions remain to understand how Hour of Code can improve to meet its goals, expanding access to computer science to all students.

KEYWORDS:

• Computer science education
• Hour of Code
• computational thinking
• retention of flow
• diversity in tech
• learning trajectories
• Cs Ed week

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Jessica Yauney

Jessica Yauney is a graduate student in the Department of Technology at Brigham Young University and a former Computer Science high school teacher. Her research centers on computer science secondary education. She can be reached at [email protected]

Scott R. Bartholomew

Scott R. Bartholomew is an assistant professor of Technology & Engineering Studies at Brigham Young University and a former Technology & Engineering middle school teacher. His research centers on the use of adaptive comparative judgment for student learning, STEM teacher professional development, PBL curriculum, and open-ended design assessment. He can be reached at [email protected].

Peter Rich

Peter Rich, PhD is an associate professor of Instructional Psychology & Technology at Brigham Young, University. Peter has taught courses on the design, development, and psychology of instruction since 2007. His research focuses on how to prepare teachers and K-12 students to think computationally by learning to code. This work is rooted in Peter’s theory of convergent cognition, which seeks to explain the effect of learning two complementary subjects on a student’s cognition. Peter’s research seeks to highlight, understand, and ultimately, improve policy, practice, and research around computing education and how computing can enhance and transform learning. He can be reached at [email protected]