Using Predicted Academic Performance to Identify At-Risk Students in Public Schools
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| Title: | Using Predicted Academic Performance to Identify At-Risk Students in Public Schools |
|---|---|
| Language: | English |
| Authors: | Ishtiaque Fazlul, Cory Koedel, Eric Parsons |
| Source: | Educational Evaluation and Policy Analysis. 2025 47(2):458-476. |
| Availability: | SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com |
| Peer Reviewed: | Y |
| Page Count: | 19 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | At Risk Students, Public Schools, Identification, Academic Achievement, Predictive Measurement, Measurement Techniques, Low Achievement |
| Geographic Terms: | Missouri |
| DOI: | 10.3102/01623737231212163 |
| ISSN: | 0162-3737 1935-1062 |
| Abstract: | Measures of student disadvantage--or risk--are critical components of equity-focused education policies. However, the risk measures used in contemporary policies have significant limitations, and despite continued advances in data infrastructure and analytic capacity, there has been little innovation in these measures for decades. We develop a new measure of student risk for use in education policies, which we call Predicted Academic Performance (PAP). PAP is a flexible, data-rich indicator that identifies students at risk of poor academic outcomes. It blends concepts from emerging early warning systems with principles of incentive design to balance the competing priorities of accurate risk measurement and suitability for policy use. In proof-of-concept policy simulations using data from Missouri, we show PAP is more effective than common alternatives at identifying students who are at risk of poor academic outcomes and can be used to target resources toward these students--and students who belong to several other associated risk categories--more efficiently. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1471330 |
| Database: | ERIC |
| FullText | Text: Availability: 0 |
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| Header | DbId: eric DbLabel: ERIC An: EJ1471330 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Using Predicted Academic Performance to Identify At-Risk Students in Public Schools – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Ishtiaque+Fazlul%22">Ishtiaque Fazlul</searchLink><br /><searchLink fieldCode="AR" term="%22Cory+Koedel%22">Cory Koedel</searchLink><br /><searchLink fieldCode="AR" term="%22Eric+Parsons%22">Eric Parsons</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Educational+Evaluation+and+Policy+Analysis%22"><i>Educational Evaluation and Policy Analysis</i></searchLink>. 2025 47(2):458-476. – Name: Avail Label: Availability Group: Avail Data: SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: https://sagepub.com – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 19 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22At+Risk+Students%22">At Risk Students</searchLink><br /><searchLink fieldCode="DE" term="%22Public+Schools%22">Public Schools</searchLink><br /><searchLink fieldCode="DE" term="%22Identification%22">Identification</searchLink><br /><searchLink fieldCode="DE" term="%22Academic+Achievement%22">Academic Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Predictive+Measurement%22">Predictive Measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement+Techniques%22">Measurement Techniques</searchLink><br /><searchLink fieldCode="DE" term="%22Low+Achievement%22">Low Achievement</searchLink> – Name: Subject Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Missouri%22">Missouri</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.3102/01623737231212163 – Name: ISSN Label: ISSN Group: ISSN Data: 0162-3737<br />1935-1062 – Name: Abstract Label: Abstract Group: Ab Data: Measures of student disadvantage--or risk--are critical components of equity-focused education policies. However, the risk measures used in contemporary policies have significant limitations, and despite continued advances in data infrastructure and analytic capacity, there has been little innovation in these measures for decades. We develop a new measure of student risk for use in education policies, which we call Predicted Academic Performance (PAP). PAP is a flexible, data-rich indicator that identifies students at risk of poor academic outcomes. It blends concepts from emerging early warning systems with principles of incentive design to balance the competing priorities of accurate risk measurement and suitability for policy use. In proof-of-concept policy simulations using data from Missouri, we show PAP is more effective than common alternatives at identifying students who are at risk of poor academic outcomes and can be used to target resources toward these students--and students who belong to several other associated risk categories--more efficiently. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2025 – Name: AN Label: Accession Number Group: ID Data: EJ1471330 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1471330 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3102/01623737231212163 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 19 StartPage: 458 Subjects: – SubjectFull: At Risk Students Type: general – SubjectFull: Public Schools Type: general – SubjectFull: Identification Type: general – SubjectFull: Academic Achievement Type: general – SubjectFull: Predictive Measurement Type: general – SubjectFull: Measurement Techniques Type: general – SubjectFull: Low Achievement Type: general – SubjectFull: Missouri Type: general Titles: – TitleFull: Using Predicted Academic Performance to Identify At-Risk Students in Public Schools Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Ishtiaque Fazlul – PersonEntity: Name: NameFull: Cory Koedel – PersonEntity: Name: NameFull: Eric Parsons IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 0162-3737 – Type: issn-electronic Value: 1935-1062 Numbering: – Type: volume Value: 47 – Type: issue Value: 2 Titles: – TitleFull: Educational Evaluation and Policy Analysis Type: main |
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