Value-Added Models (VAMs) require consistent longitudinal data that includes student test scores coming from sequential years. However, longitudinal data is usually incomplete for
several reasons, including year-to-year changes in student populations. This study explores the implications of yearly population changes on teacher VAM scores. I used the North Carolina
End of Grade student data sets, created artificial sub-samples, and run separate VAMs for each sub-sample. Results of this study indicate that changes in student population could affect
teacher VAM scores. / A Dissertation submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the Doctor of Philosophy. / Fall Semester 2015. / November 12, 2015. / hierarchical linear modeling, Value-added models / Includes bibliographical references. / Russell Almond, Professor Directing Dissertation; Elizabeth Jakubowski, University Representative; Betsy Jane Becker, Committee Member; Insu Paek,
Committee Member.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_291283 |
| Contributors | Yurekli, Hulya (authoraut), Almond, Russell G. (professor directing dissertation), Jakubowski, Elizabeth M. (university representative), Becker, Betsy Jane, 1956- (committee member), Paek, Insu (committee member), Florida State University (degree granting institution), College of Education (degree granting college), Department of Educational Psychology and Learning Systems (degree granting department) |
| Publisher | Florida State University |
| Source Sets | Florida State University |
| Language | English, English |
| Detected Language | English |
| Type | Text, text |
| Format | 1 online resource (128 pages), computer, application/pdf |
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