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ERIC Number: EJ1031353
Record Type: Journal
Publication Date: 2014
Pages: 9
Abstractor: As Provided
Reference Count: N/A
ISSN: ISSN-0731-1745
Evaluating the Predictive Value of Growth Prediction Models
Murphy, Daniel L.; Gaertner, Matthew N.
Educational Measurement: Issues and Practice, v33 n2 p5-13 Sum 2014
This study evaluates four growth prediction models--projection, student growth percentile, trajectory, and transition table--commonly used to forecast (and give schools credit for) middle school students' future proficiency. Analyses focused on vertically scaled summative mathematics assessments, and two performance standards conditions (high rigor and low rigor) were examined. Results suggest that, when "status plus growth" is the accountability metric a state uses to reward or sanction schools, growth prediction models offer value above and beyond status-only accountability systems in most, but not all, circumstances. Predictive growth models offer little value beyond status-only systems if the future target proficiency cut score is rigorous. Conversely, certain models (e.g., projection) provide substantial additional value when the future target cut score is relatively low. In general, growth prediction models' predictive value is limited by a lack of power to detect students who are truly on-track. Limitations and policy implications are discussed, including the utility of growth projection models in assessment and accountability systems organized around ambitious college-readiness goals.
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Publication Type: Journal Articles; Reports - Research
Education Level: Middle Schools; Junior High Schools; Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A