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Exploration of the Predictive Validity of Middle School Math Screeners.

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Title: Exploration of the Predictive Validity of Middle School Math Screeners.
Authors: Van Norman, Ethan R. (AUTHOR), Klingbeil, David A. (AUTHOR), Crespy, Hannah K. (AUTHOR)
Source: Psychology in the Schools. Feb2026, Vol. 63 Issue 2, p423-432. 10p.
Subjects: Predictive validity, Curriculum-based assessment, Mathematics exams, Academic achievement, Middle schools, Mathematical ability testing, Quantile regression, Theory-practice relationship
Abstract: Universal screening is a key element of multi‐tiered systems of support. Relative to literacy, fewer studies have investigated the psychometric properties of math assessments particularly amongst middle school students. We investigated whether outcomes from two types of curriculum‐based measures (CBMs), computational fluency (M‐COMP) and concepts and application (M‐CAP) were predictive of end of year test scores after accounting for performance on a computer adaptive test of broad math performance (Measures of Academic Progress—MAP). We used quantile regression to determine whether M‐COMP and M‐CAP were differentially important in predicting end of year scores as a function of overall student skill level (e.g., students performing far below expectations) after accounting for MAP scores. Including M‐COMP consistently improved predictions of end of year state test scores for grade six students scoring below the 25th percentile on an end of year achievement test. M‐COMP and M‐CAP provided limited additional predictive utility across skill levels for students in grades seven and eight. Summary: Schools can use computer adaptive tests (CATs) or curriculum‐based measures (CBMs) to identify middle school students at‐risk for later difficulties and in need of supplemental support in math.For schools that are already using CATs, administering additional CBMs adds little values in predicting end of year performance for most students.Some exceptions were observed in Grade 6 students who were performing far bellow average. [ABSTRACT FROM AUTHOR]
Copyright of Psychology in the Schools is the property of Wiley-Blackwell 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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DbLabel: Psychology and Behavioral Sciences Collection
An: 190792017
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Exploration of the Predictive Validity of Middle School Math Screeners.
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  Data: <searchLink fieldCode="AR" term="%22Van+Norman%2C+Ethan+R%2E%22">Van Norman, Ethan R.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Klingbeil%2C+David+A%2E%22">Klingbeil, David A.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Crespy%2C+Hannah+K%2E%22">Crespy, Hannah K.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Psychology+in+the+Schools%22">Psychology in the Schools</searchLink>. Feb2026, Vol. 63 Issue 2, p423-432. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Predictive+validity%22">Predictive validity</searchLink><br /><searchLink fieldCode="DE" term="%22Curriculum-based+assessment%22">Curriculum-based assessment</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematics+exams%22">Mathematics exams</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+achievement%22">Academic achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Middle+schools%22">Middle schools</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+ability+testing%22">Mathematical ability testing</searchLink><br /><searchLink fieldCode="DE" term="%22Quantile+regression%22">Quantile regression</searchLink><br /><searchLink fieldCode="DE" term="%22Theory-practice+relationship%22">Theory-practice relationship</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Universal screening is a key element of multi‐tiered systems of support. Relative to literacy, fewer studies have investigated the psychometric properties of math assessments particularly amongst middle school students. We investigated whether outcomes from two types of curriculum‐based measures (CBMs), computational fluency (M‐COMP) and concepts and application (M‐CAP) were predictive of end of year test scores after accounting for performance on a computer adaptive test of broad math performance (Measures of Academic Progress—MAP). We used quantile regression to determine whether M‐COMP and M‐CAP were differentially important in predicting end of year scores as a function of overall student skill level (e.g., students performing far below expectations) after accounting for MAP scores. Including M‐COMP consistently improved predictions of end of year state test scores for grade six students scoring below the 25th percentile on an end of year achievement test. M‐COMP and M‐CAP provided limited additional predictive utility across skill levels for students in grades seven and eight. Summary: Schools can use computer adaptive tests (CATs) or curriculum‐based measures (CBMs) to identify middle school students at‐risk for later difficulties and in need of supplemental support in math.For schools that are already using CATs, administering additional CBMs adds little values in predicting end of year performance for most students.Some exceptions were observed in Grade 6 students who were performing far bellow average. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Psychology in the Schools is the property of Wiley-Blackwell 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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=190792017
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        Value: 10.1002/pits.70101
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        Text: English
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      – SubjectFull: Curriculum-based assessment
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      – SubjectFull: Mathematics exams
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      – SubjectFull: Academic achievement
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      – SubjectFull: Middle schools
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      – SubjectFull: Mathematical ability testing
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      – SubjectFull: Quantile regression
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      – SubjectFull: Theory-practice relationship
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      – TitleFull: Exploration of the Predictive Validity of Middle School Math Screeners.
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            NameFull: Van Norman, Ethan R.
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            NameFull: Klingbeil, David A.
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              Text: Feb2026
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              Y: 2026
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