Cited by 139Educational Assessment and ImprovementSchool Choice and PerformanceEducation Discipline and Inequality

Opening or closing doors for students? Equity and data use in schools

Datnow, Amanda, Park, Vicki·2018·Journal of Educational Change

Integrity signals

Registry

Crossref · 10.1007/s10833-018-9323-6

Cites

8 of 8 references verified0 citation errors · 0 not checkable

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  • Symbolic data use, misuse and abuse are often consequences of an overly strong focus on accountability instead of on improvement.

    “Symbolic data use, misuse and abuse are often consequences of an overly strong focus on accountability instead of on improvement (Datnow and Park 2018).”

    From Data-based decision-making for school improvement: Research insights and gaps (2019) · cites this paper as Datnow and Park 2018

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Authors
Datnow, A., & Park, V.
Affiliations
  • University of California San Diego (US)
  • San Jose State University (US)
Corresponding author
Datnow, Amanda
Venue
Journal of Educational Change
Published
2018-04-30
Volume
19
Issue
2
Pages
131-152
ISSN
  • 1389-2843 (ISSN-L)
  • 1573-1812
OpenAlex
W2800816280
Cited by
139
References
8
Citations by year
2026: 22 · 2025: 17 · 2024: 23 · 2023: 11 · 2022: 21 · 2021: 16 · 2020: 18 · 2019: 11
FWCI
15.12
Type
journal article
Language
en
Open access
closed
Locations
Journal of Educational Change (publishedVersion)
Funders
Spencer Foundation
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
  • Social Sciences › Education › School Choice and Performance
  • Social Sciences › Education › Education Discipline and Inequality
Keywords
educational data use, educational equity, school accountability, continuous improvement, data-driven decision making, student tracking, flexible grouping, student development, educational decision-making

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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