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[Preprint] The Middle-to-High School Transition: Key Factors Shaping 9th-Grade Computer Science Enrollment

David J. Amiel & Cynthia L. Blitz

This study examines the critical transition from middle school to high school as a pivotal decision point in computer science education. Analyzing data from 5,505 students across eight diverse school districts, researchers identified several key factors that influence 9th-grade CS enrollment. High academic achievers, male students, Asian students, and those with prior exposure to computer science and Algebra 1 in middle school were significantly more likely to enroll in 9th-grade CS courses. Conversely, female students, English Language Learners, and students receiving special education services showed lower participation rates.


The findings highlight that despite improvements in CS course availability, persistent barriers to participation extend beyond mere access. The research suggests that middle schools should ensure all 8th graders are aware of CS options during course selection, with targeted outreach for underrepresented groups. Additionally, schools should address misconceptions about CS being inherently difficult and exclusively for top academic performers, while ensuring support systems don't inadvertently create barriers to CS participation.


By focusing on this critical transition period, the study provides actionable strategies for schools to assess the effectiveness of early CS initiatives and implement targeted interventions to promote more equitable participation in computer science education.

February 2025

Note: This is a non-peer-reviewed preprint. Journal & DOI will be added following publication.

The study identifies key factors influencing 9th-grade computer science enrollment, revealing persistent participation gaps and providing actionable strategies to promote equity during the middle-to-high school transition.

Citation

Amiel,  D., &  Blitz,  C. (2025). The Middle-to-High School Transition: Key Factors Shaping 9th-Grade Computer Science Enrollment. Preprints. https://doi.org/10.20944/preprints202502.0955.v1z

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