Diving Into Students' Transcripts: High School Course‐Taking Sequences and Postsecondary Enrollment.
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| Title: | Diving Into Students' Transcripts: High School Course‐Taking Sequences and Postsecondary Enrollment. |
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| Authors: | Ogut, Burhan1 (AUTHOR) bogut@air.org, Circi, Ruhan1 (AUTHOR) rcirci@air.org |
| Source: | Educational Measurement: Issues & Practice. Jun2023, Vol. 42 Issue 2, p21-31. 11p. 1 Diagram, 7 Charts. |
| Subject Terms: | *High schools, *Language arts, *College enrollment, Logistic regression analysis, Random forest algorithms |
| Abstract: | The purpose of this study was to explore high school course‐taking sequences and their relationship to college enrollment. Specifically, we implemented sequence analysis to discover common course‐taking trajectories in math, science, and English language arts using high school transcript data from a recent nationally representative survey. Through sequence clustering, we reduced the complexity of the sequences and examined representative course‐taking sequences. Classification tree, random forests, and multinomial logistic regression analyses were used to explore the relationship between the course sequences students complete and their postsecondary outcomes. Results showed that distinct representative course‐taking sequences can be identified for all students as well as student subgroups. More advanced and complex course‐taking sequences were associated with postsecondary enrollment. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
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| Abstract: | The purpose of this study was to explore high school course‐taking sequences and their relationship to college enrollment. Specifically, we implemented sequence analysis to discover common course‐taking trajectories in math, science, and English language arts using high school transcript data from a recent nationally representative survey. Through sequence clustering, we reduced the complexity of the sequences and examined representative course‐taking sequences. Classification tree, random forests, and multinomial logistic regression analyses were used to explore the relationship between the course sequences students complete and their postsecondary outcomes. Results showed that distinct representative course‐taking sequences can be identified for all students as well as student subgroups. More advanced and complex course‐taking sequences were associated with postsecondary enrollment. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 07311745 |
| DOI: | 10.1111/emip.12554 |