Community College Transfer Admission and Articulation in a Selective STEM Major: How University Faculty, Staff, and Administrators Contribute to Hypercompetitive and Convoluted Transfer Processes.

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Title: Community College Transfer Admission and Articulation in a Selective STEM Major: How University Faculty, Staff, and Administrators Contribute to Hypercompetitive and Convoluted Transfer Processes.
Authors: Blaney, Jennifer M. (AUTHOR)
Source: Journal of Higher Education. 2026, Vol. 97 Issue 3, p620-645. 26p.
Subjects: Transfer students, University & college admission, STEM occupations, Rational-legal authority, University faculty, Academic freedom
Abstract: Drawing on interview data from 20 faculty, staff, and administrators across five universities, this study identifies how university agents shape community college transfer pathways into highly competitive computer science majors. Applying the concept of street-level bureaucracy and using phenomenological methods to center the meaning making of university decision makers, the findings reveal how university agents create hyper-competitive admissions processes to manage capacity constraints. Other findings show how departments prioritize faculty autonomy when setting transfer requirements, leading to inconsistent requirements across university transfer destinations, despite state- and system-level policies designed to streamline transfer admission and articulation. I further discuss how university faculty and administrators make decisions that lead to extended bureaucratic procedures for processing transfer students' credit articulations, placing burdens on students and departmental staff. Implications focus on the importance of creating a shared sense of responsibility among university actors for facilitating transfer student success and other strategies for universities to build more accessible transfer pathways into STEM majors. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Higher Education is the property of Taylor & Francis Ltd 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: Psychology and Behavioral Sciences Collection
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  Data: Drawing on interview data from 20 faculty, staff, and administrators across five universities, this study identifies how university agents shape community college transfer pathways into highly competitive computer science majors. Applying the concept of street-level bureaucracy and using phenomenological methods to center the meaning making of university decision makers, the findings reveal how university agents create hyper-competitive admissions processes to manage capacity constraints. Other findings show how departments prioritize faculty autonomy when setting transfer requirements, leading to inconsistent requirements across university transfer destinations, despite state- and system-level policies designed to streamline transfer admission and articulation. I further discuss how university faculty and administrators make decisions that lead to extended bureaucratic procedures for processing transfer students' credit articulations, placing burdens on students and departmental staff. Implications focus on the importance of creating a shared sense of responsibility among university actors for facilitating transfer student success and other strategies for universities to build more accessible transfer pathways into STEM majors. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Higher Education is the property of Taylor & Francis Ltd 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: 10.1080/00221546.2025.2497185
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      – Code: eng
        Text: English
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      – SubjectFull: Transfer students
        Type: general
      – SubjectFull: University & college admission
        Type: general
      – SubjectFull: STEM occupations
        Type: general
      – SubjectFull: Rational-legal authority
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      – SubjectFull: University faculty
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      – SubjectFull: Academic freedom
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              Text: 2026
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