Cited by 407Educational Assessment and ImprovementTeacher Education and Leadership StudiesEvaluation of Teaching Practices

Data-informed curriculum reform: Which data, what purposes, and promoting and hindering factors

Schildkamp, Kim, Kuiper, Wilmad·2010·Teaching and Teacher Education

Integrity signals

Registry

Crossref · 10.1016/j.tate.2009.06.007

Cites

52 of 52 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Data use for educational decision making has become more prevalent than ever.

    “The use of data for educational decision making has never been more prevalent”

    From Data teams for school improvement (2016) · cites this paper as Schildkamp & Kuiper, 2010

  • Teachers often do not use data as well as they could, or do not use it at all.

    “teachers often do not use data to its best effect, if at all”

    From Data teams for school improvement (2016) · cites this paper as Schildkamp & Kuiper, 2010

  • Dutch schools can use several data sources to improve education, including intake, transfer, school leaver, inspection, self-evaluation, assessment, examination, and questionnaire data.

    “Dutch schools can use several data sources to improve their education, such as data on intake, transfer, and school leavers; school inspection and selfevaluation data; assessment and examination results; and student and parent questionnaire data”

    From Data teams for school improvement (2016) · cites this paper as Schildkamp & Kuiper, 2010

  • Teachers need to be able to transform data into information based on their analysis and interpretation of the data, including identifying student learning needs and determining appropriate actions.

    “Further, teachers need to be able to transform data into information based on their analysis and interpretation of the data.This step concerns identifying student learning needs”
  • When goals are clear and measurable for both teachers and students, assessment data can provide teachers and students with feedback on their progress with regard to these goals.

    “When the goals are clear and measurable for both teachers and students, (assessment) data can provide teachers and students with feedback on their progress with regard to these goals”

Cites

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3 of the 55 references couldn’t be matched to a known paper.

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Authors
Schildkamp, K., & Kuiper, W.
Affiliations
  • University of Twente (NL)
  • Utrecht University (NL)
Corresponding author
Schildkamp, Kim
Venue
Teaching and Teacher Education
Publisher
Elsevier BV
Published
2010-04
Volume
26
Issue
3
Pages
482-496
ISSN
0742-051X (ISSN-L)
OpenAlex
W2133878615
Cited by
406
References
55
Citations by year
2026: 14 · 2025: 19 · 2024: 23 · 2023: 18 · 2022: 33 · 2021: 29 · 2020: 30 · 2019: 35 · 2018: 24 · 2017: 38 · 2016: 33 · 2015: 30 · 2014: 16 · 2013: 25 · 2012: 26
FWCI
28.29
Type
journal article
Language
en
Open access
closed
Locations
  • Teaching and Teacher Education (publishedVersion)
  • University of Twente Research Information (publishedVersion)
  • University of Twente Research Information (submittedVersion)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
  • Social Sciences › Education › Teacher Education and Leadership Studies
  • Social Sciences › Education › Evaluation of Teaching Practices
Keywords
data-driven decision making, curriculum reform, educational data use, classroom data, school data, instructional decision-making, school leadership, school improvement, school policy development

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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.

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