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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.
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]
Copyright of Educational Measurement: Issues & Practice is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Diving Into Students' Transcripts: High School Course‐Taking Sequences and Postsecondary Enrollment.
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  Data: <searchLink fieldCode="AR" term="%22Ogut%2C+Burhan%22">Ogut, Burhan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> bogut@air.org</i><br /><searchLink fieldCode="AR" term="%22Circi%2C+Ruhan%22">Circi, Ruhan</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> rcirci@air.org</i>
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  Data: <searchLink fieldCode="JN" term="%22Educational+Measurement%3A+Issues+%26+Practice%22">Educational Measurement: Issues & Practice</searchLink>. Jun2023, Vol. 42 Issue 2, p21-31. 11p. 1 Diagram, 7 Charts.
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  Data: *<searchLink fieldCode="DE" term="%22High+schools%22">High schools</searchLink><br />*<searchLink fieldCode="DE" term="%22Language+arts%22">Language arts</searchLink><br />*<searchLink fieldCode="DE" term="%22College+enrollment%22">College enrollment</searchLink><br /><searchLink fieldCode="DE" term="%22Logistic+regression+analysis%22">Logistic regression analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Random+forest+algorithms%22">Random forest algorithms</searchLink>
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  Data: 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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  Data: <i>Copyright of Educational Measurement: Issues & Practice is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/emip.12554
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        Text: English
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      – SubjectFull: High schools
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      – SubjectFull: Language arts
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      – SubjectFull: College enrollment
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      – SubjectFull: Logistic regression analysis
        Type: general
      – SubjectFull: Random forest algorithms
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      – TitleFull: Diving Into Students' Transcripts: High School Course‐Taking Sequences and Postsecondary Enrollment.
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              Text: Jun2023
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