Data in Practice: Conceptualizing the Data-Based Decision-Making Phenomena
Abstract
“Data use” and “data-based decision making” are increasingly popular mantras in public policy discourses and texts. Policy makers place tremendous faith in the power of data to transform practice, but the fate of policy makers’ efforts will depend in great measure on the very practice they hope to move. In most conversations about data use, however, relations between data and practice have been underconceptualized. In this essay, I identify and discuss some conceptual and analytical tools for studying data in practice by drawing on work from various theoretical traditions. I explore some ways in which we might frame a research agenda in order to investigate data in everyday practice in schools. My account is centered on schoolhouse work practice, but the research apparatus I consider can be applied to practice in other organizations in the education sector and indeed to interorganizational practice, a critical consideration in the education sector.
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Data do not objectively guide decisions by themselves.
“According to Spillane (2012), “data do not objectively guide decisions on their own” (p.114).”
From Data teams for school improvement (2016) · cites this paper as Spillane (2012)
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References 95 · Cited by 308
- Authors
- Spillane, J. P.
- Affiliations
- Northwestern University (US)
- Corresponding author
- Spillane, James P.
- ORCID
- Spillane, James P.
- Venue
- American Journal of Education
- Publisher
- University of Chicago Press
- Published
- 2012-02
- Volume
- 118
- Issue
- 2
- Pages
- 113-141
- ISSN
- 0195-6744 (ISSN-L)
- 1549-6511
- OpenAlex
- W2114377232
- Cited by
- 308
- References
- 95
- Citations by year
- 2026: 14 · 2025: 9 · 2024: 12 · 2023: 11 · 2022: 36 · 2021: 22 · 2020: 33 · 2019: 22 · 2018: 31 · 2017: 35 · 2016: 22 · 2015: 25 · 2014: 19 · 2013: 13 · 2012: 3
- FWCI
- 39.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Journal of Education (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Social Sciences › Political Science and International Relations › Global Educational Policies and Reforms
- Social Sciences › Decision Sciences › Management Science and Operations Research › Evaluation and Performance Assessment
- Keywords
- data-driven decision making, data utilization, school decision-making, education policy, research agenda
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.
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