Teachers’ Sensemaking of Data and Implications for Equity
Abstract
This article examines an understudied aspect of teachers’ sensemaking of student learning data: the way in which teachers explain the causes of the outcomes observed in data. Drawing on sensemaking and attribution theory and data collected in six middle schools, we find that while teachers most often attributed outcomes to their own instruction, they also frequently focused on supposedly stable student characteristics. By citing these characteristics as explanations for the results analyzed, teachers may have inhibited reflection on their practice and reinforced low expectations for English language learners (ELLs) and students in special education. These findings yield implications for (a) the effectiveness of data use reforms and (b) equity in the education of ELLs and students in special education.
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Sense-making is not a straightforward or exclusively rational process.
“Sense-making is not a straightforward or exclusively rational process (Bertrand and Marsh 2015; Kahneman and Frederick 2005).”
From Data-based decision-making for school improvement: Research insights and gaps (2019) · cites this paper as Bertrand and Marsh 2015
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- Authors
- Bertrand, M., & Marsh, J. A.
- Affiliations
- Arizona State University (US)
- University of Southern California (US)
- Venue
- American Educational Research Journal
- Published
- 2015-10
- Volume
- 52
- Issue
- 5
- Pages
- 861-893
- ISSN
- 0002-8312 (ISSN-L)
- 1935-1011
- OpenAlex
- W1955103787
- Cited by
- 209
- References
- 70
- Citations by year
- 2026: 18 · 2025: 22 · 2024: 19 · 2023: 14 · 2022: 25 · 2021: 19 · 2020: 25 · 2019: 25 · 2018: 17 · 2017: 18 · 2016: 7
- FWCI
- 27.50
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- American Educational Research Journal (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Social Sciences › Education › Teacher Education and Leadership Studies
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- teacher sensemaking, student learning data, attribution theory, English language learners, special education students, low expectations, educational equity, junior high school teachers, teacher reflection
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