Strategic Framing: How Leaders Craft the Meaning of Data Use for Equity and Learning
Abstract
Although there is an emerging body of research that examines data-driven decision making (DDDM) in schools, little attention has been paid to how local leaders strategically frame sensemaking around data use. This exploratory case examines how district and school leaders consciously framed the implementation of DDDM in one urban high school. Leaders strategically constructed diagnostic, motivating, and prognostic frames to promote a culture of using data for continuous improvement. Our findings demonstrate that leaders developed (a) diagnostic frames centered on the need to confront student achievement and opportunity gaps; (b) motivating frames concentrated on school improvement as shared collective responsibility; and (c) prognostic frames focused on making incremental change to sustain reform efforts and the creation of common goals to monitor progress. The findings suggest that framing is an important leadership tactic that needs careful consideration when reforms are introduced and implemented.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
A compliance orientation towards data use will not lead to authentic or sustained data use.
“To build a data use culture, school leaders need to recognise that a compliance orientation towards data use will not lead to authentic or sustained data use (Park, et al., 2013).”
From Data-based decision-making for school improvement: Research insights and gaps (2019) · cites this paper as Park, et al., 2013
Data use should not focus solely on achievement and deficits of student capabilities, but should also focus on students' strengths.
“it is important that data use does not focus solely on achievement and the de fi cits of student capabilities, but that it also focuses on students ' strengths (Park et al., 2013).”
From Data-based decision-making for school improvement: Research insights and gaps (2019) · cites this paper as Park et al., 2013
Critical dialogue between different stakeholders is crucial for data use.
“Critical dialogue between di ff erent stakeholders is crucial here”
From Data-based decision-making for school improvement: Research insights and gaps (2019) · cites this paper as Park et al., 2013
Cites
Hartley, J. (2004) · Essential Guide to Qualitative Methods in Organizational Research · doi:10.4135/9781446280119.n26 · Cited by 15,461 · see citing works
Below the Bubble: “Educational Triage” and the Texas Accountability System
Booher-Jennings, J. (2005) · American Educational Research Journal · doi:10.3102/00028312042002231 · Cited by 762 · cited 2× · see citing works
“(Booher-Jennings, 2005; Diamond & Cooper, 2007).”
BackgroundDetracking: The Social Construction of Ability, Cultural Politics, and Resistance to Reform
Oakes, J., Wells, A. S., Jones, M., & Datnow, A. (1997) · Teachers College Record: The Voice of Scholarship in Education · doi:10.1177/016146819709800305 · Cited by 361 · cited 1× · see citing works
“Studies on past reforms found that without critical dialogue offering alternative views, the dominant deficit-model construction of students’ capabilities were reinforced and reproduced (Lipman, 1997; Oakes et al., 1997).”
BackgroundKerr, K. A., Marsh, J. A., Ikemoto, G. S., Darilek, H., & Barney, H. (2006) · American Journal of Education · doi:10.1086/505057 · Cited by 341 · see citing works
Teachers’ Use of Data: Loose Coupling, Agenda Setting, and Team Norms
Young, V. M. (2006) · American Journal of Education · doi:10.1086/505058 · Cited by 281 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Data-based decision-making for school improvement: Research insights and gaps
Schildkamp, K. (2019) · Educational Research · doi:10.1080/00131881.2019.1625716 · Cited by 347 · see citing works
Datnow, A., & Hubbard, L. (2016) · Journal of Educational Change · doi:10.1007/s10833-015-9264-2 · Cited by 287 · see citing works
Datnow, A., & Hubbard, L. (2015) · Teachers College Record: The Voice of Scholarship in Education · doi:10.1177/016146811511700408 · Cited by 176 · see citing works
Jimerson, J. B. (2014) · Studies in Educational Evaluation · doi:10.1016/j.stueduc.2013.10.010 · Cited by 97 · see citing works
How Do Teachers Make Sense of Data in the Context of High-Stakes Decision Making?
Vanlommel, K., & Schildkamp, K. (2019) · American Educational Research Journal · doi:10.3102/0002831218803891 · Cited by 79 · see citing works
Data literacy and learning analytics
Mandinach, E. B., & Abrams, L. M. (2022) · The Handbook of Learning Analytics · doi:10.18608/hla22.019 · Cited by 22 · see citing works
- Authors
- Park, V., Daly, A. J., & Guerra, A. W.
- Affiliations
- University of California San Diego (US)
- Venue
- Educational Policy
- Publisher
- SAGE Publications
- Published
- 2012-05-07
- Volume
- 27
- Issue
- 4
- Pages
- 645-675
- ISSN
- 0895-9048 (ISSN-L)
- 1552-3896
- OpenAlex
- W2136965145
- Cited by
- 134
- References
- 5
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 10 · 2023: 6 · 2022: 12 · 2021: 12 · 2020: 19 · 2019: 16 · 2018: 12 · 2017: 15 · 2016: 8 · 2015: 8 · 2014: 2 · 2013: 2 · 2012: 1
- FWCI
- 8.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Educational Policy (publishedVersion)
- Funders
- Bill and Melinda Gates Foundation
- NewSchools Venture Fund
- William and Flora Hewlett Foundation
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Social Sciences › Education › Educational Leadership and Practices
- Social Sciences › Education › Teacher Education and Leadership Studies
- Keywords
- strategic framing, data-driven decision making, school leadership, sensemaking, continuous improvement, educational reform, opportunity gap, urban high schools, district leaders, school leaders
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review