Document Type
Article
Publication Date
2019
Abstract
The purpose of this research is to examine the relationship between students’ participation in the two high school AP computer science exam options and their selected fields of study once they enter post-secondary education. Two studies using national public-use datasets of participation and performance were conducted. Study 1 compared score distributions for the traditional Computer Science A exam to those of the newer Computer Science Principles exam during its first two years of implementation. In Study 1, Chi-square analyses revealed large differences in performance between the two exams, with the Computer Science Principles scores clustering more around marginal pass rates. Descriptive data indicate that African American, Latino, and female students participated in larger proportions on the new exam, whereas traditionally overrepresented groups are continuing to opt more for the traditional Computer Science A course. In Study 2, logistic regression analyses were conducted on the 2016 second follow-up data collection of the High School Longitudinal Study 2009 (HSLS:09). Those analyses revealed that 11th Grade enrollment in computer science courses that concentrate on computer programming significantly predicted selection of a STEM major as the first declared major after high school. Although students who enrolled in Computer Science A were five times as likely to declare a STEM major, a comparison of the curricula and assessments for the two courses suggests that the Computer Science Principles exam places far less emphasis on programming. The potential implications of the differential foci and emphases of the two courses are discussed.
Recommended Citation
Howard, K. E., & Havard, D. D. (2019). Advanced Placement (AP) Computer Science Principles: Searching for Equity in a Two-Tiered Solution to Underrepresentation. Journal of Computer Science Integration, 2(1), 1-15. https://doi.org/10.26716/jcsi.2019.02.1.1
Peer Reviewed
1
Copyright
The authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Included in
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Comments
This article was originally published in Journal of Computer Science Integration, volume 2, issue 1, in 2019. DOI: 10.26716/jcsi.2019.02.1.1