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Prediction of Radiography Certification Examination Scores Using Astin's Input-Environment-Output Model

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Title: Prediction of Radiography Certification Examination Scores Using Astin's Input-Environment-Output Model
Language: English
Authors: Barymon, Deanna M.
Source: ProQuest LLC. 2022Ed.D. Dissertation, University of Arkansas.
Availability: ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml
Peer Reviewed: N
Page Count: 53
Publication Date: 2022
Document Type: Dissertations/Theses - Doctoral Dissertations
Education Level: Higher Education
Postsecondary Education
Descriptors: Prediction, Certification, Scores, Radiology, Licensing Examinations (Professions), College Students, Allied Health Occupations Education, Reading Comprehension, Mathematics Achievement, Grade Point Average, Science Achievement
Geographic Terms: Arkansas
ISBN: 979-83-7440-785-3
Abstract: Numerous health profession fields, including radiology, have attempted to identify predictors of success on their respective credentialing exams. This preregistered study seeks to determine if available academic performance measures may predict radiography national certification examination scores and help educators identify students for remediation and support. The study will use the Astin Input-Environment-Output Model, which ascertains that student outcomes are a result of what they bring into an academic program and the environment experienced during the program. The non-experimental retrospective study will look at the 2018 to 2021 Arkansas State University radiography cohorts. Multiple regression will be used to determine if reading comprehension, final course grade in college algebra, GPA in prerequisite sciences courses, and final grade in Image Acquisition and Evaluation II can predict success on the radiography certification examination. Findings from this study will help guide program admission criteria and identify students for remediation and support before taking the certification examination. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
Abstractor: As Provided
Entry Date: 2023
Access URL: https://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:29397639
Accession Number: ED631460
Database: ERIC
FullText Text:
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  Data: Prediction of Radiography Certification Examination Scores Using Astin's Input-Environment-Output Model
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  Data: <searchLink fieldCode="DE" term="%22Prediction%22">Prediction</searchLink><br /><searchLink fieldCode="DE" term="%22Certification%22">Certification</searchLink><br /><searchLink fieldCode="DE" term="%22Scores%22">Scores</searchLink><br /><searchLink fieldCode="DE" term="%22Radiology%22">Radiology</searchLink><br /><searchLink fieldCode="DE" term="%22Licensing+Examinations+%28Professions%29%22">Licensing Examinations (Professions)</searchLink><br /><searchLink fieldCode="DE" term="%22College+Students%22">College Students</searchLink><br /><searchLink fieldCode="DE" term="%22Allied+Health+Occupations+Education%22">Allied Health Occupations Education</searchLink><br /><searchLink fieldCode="DE" term="%22Reading+Comprehension%22">Reading Comprehension</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematics+Achievement%22">Mathematics Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Grade+Point+Average%22">Grade Point Average</searchLink><br /><searchLink fieldCode="DE" term="%22Science+Achievement%22">Science Achievement</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Arkansas%22">Arkansas</searchLink>
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  Data: Numerous health profession fields, including radiology, have attempted to identify predictors of success on their respective credentialing exams. This preregistered study seeks to determine if available academic performance measures may predict radiography national certification examination scores and help educators identify students for remediation and support. The study will use the Astin Input-Environment-Output Model, which ascertains that student outcomes are a result of what they bring into an academic program and the environment experienced during the program. The non-experimental retrospective study will look at the 2018 to 2021 Arkansas State University radiography cohorts. Multiple regression will be used to determine if reading comprehension, final course grade in college algebra, GPA in prerequisite sciences courses, and final grade in Image Acquisition and Evaluation II can predict success on the radiography certification examination. Findings from this study will help guide program admission criteria and identify students for remediation and support before taking the certification examination. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
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    Languages:
      – Text: English
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      Pagination:
        PageCount: 53
    Subjects:
      – SubjectFull: Prediction
        Type: general
      – SubjectFull: Certification
        Type: general
      – SubjectFull: Scores
        Type: general
      – SubjectFull: Radiology
        Type: general
      – SubjectFull: Licensing Examinations (Professions)
        Type: general
      – SubjectFull: College Students
        Type: general
      – SubjectFull: Allied Health Occupations Education
        Type: general
      – SubjectFull: Reading Comprehension
        Type: general
      – SubjectFull: Mathematics Achievement
        Type: general
      – SubjectFull: Grade Point Average
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      – SubjectFull: Science Achievement
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      – SubjectFull: Arkansas
        Type: general
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      – TitleFull: Prediction of Radiography Certification Examination Scores Using Astin's Input-Environment-Output Model
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