Demystifying Adequate Growth Percentiles
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| Title: | Demystifying Adequate Growth Percentiles |
|---|---|
| Language: | English |
| Authors: | Katherine E. Castellano (ORCID |
| Source: | Educational Measurement: Issues and Practice. 2025 44(1):31-43. |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 13 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Student Evaluation, Growth Models, Student Educational Objectives, Educational Indicators, Federal Programs, Academic Achievement, Academic Standards, Progress Monitoring, Achievement Gains, Test Reliability, Predictor Variables, Predictive Validity |
| DOI: | 10.1111/emip.12635 |
| ISSN: | 0731-1745 1745-3992 |
| Abstract: | Growth-to-standard models evaluate student growth against the growth needed to reach a future standard or target of interest, such as proficiency. A common growth-to-standard model involves comparing the popular Student Growth Percentile (SGP) to Adequate Growth Percentiles (AGPs). AGPs follow from an involved process based on fitting a series of nonlinear quantile regression models to longitudinal student test score data. This paper demystifies AGPs by deriving them in the more familiar linear regression framework. It further shows that unlike SGPs, AGPs and on-track classifications based on AGPs are strongly related to status. Lastly, AGPs are evaluated in terms of their classification accuracy. An empirical study and analytic derivations reveal AGPs can be problematic indicators of students' future performance with previously not proficient students being more likely incorrectly flagged as not on-track and previously proficient students as on track. These classification errors have equity implications at the individual and school levels. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1460444 |
| Database: | ERIC |
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| Abstract: | Growth-to-standard models evaluate student growth against the growth needed to reach a future standard or target of interest, such as proficiency. A common growth-to-standard model involves comparing the popular Student Growth Percentile (SGP) to Adequate Growth Percentiles (AGPs). AGPs follow from an involved process based on fitting a series of nonlinear quantile regression models to longitudinal student test score data. This paper demystifies AGPs by deriving them in the more familiar linear regression framework. It further shows that unlike SGPs, AGPs and on-track classifications based on AGPs are strongly related to status. Lastly, AGPs are evaluated in terms of their classification accuracy. An empirical study and analytic derivations reveal AGPs can be problematic indicators of students' future performance with previously not proficient students being more likely incorrectly flagged as not on-track and previously proficient students as on track. These classification errors have equity implications at the individual and school levels. |
|---|---|
| ISSN: | 0731-1745 1745-3992 |
| DOI: | 10.1111/emip.12635 |
