Effects of a data-based decision making intervention on student achievement
Open accessThe claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
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-literate teachers tailor classroom instruction based on data insights.
“Specifically, data-literate teachers leverage student assessment data to evaluate learning progress (Abrams et al., 2016; Jimerson, 2014; Jimerson & Wayman, 2015; Jimerson et al., 2016; Snodgrass Rangel et al., 2016), to tailor classroom instruction based on data insights (Mokhtari et al., 2009; Poortman & Schildkamp, 2016; Staman et al., 2017; van der Scheer & Visscher, 2018), and to ensure”
From Dimensions of teachers’ data literacy: A systematic review of literature from 1990 to 2021 (2024) · cites this paper as Staman et al., 2017
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Data-informed curriculum reform: Which data, what purposes, and promoting and hindering factors
Schildkamp, K., & Kuiper, W. (2010) · Teaching and Teacher Education · doi:10.1016/j.tate.2009.06.007 · Cited by 406 · cited 1× · see citing works
“This could enhance student learning if teachers reflect (more) on the impact of the instruction they have given, and attempt to provide tailor-made instruction based on their knowledge of how students perform and which learning problems they face (Schildkamp & Kuiper, 2010).”
BackgroundIkemoto, G. S., & Marsh, J. A. (2007) · Yearbook of the National Society for the Study of Education · doi:10.1111/j.1744-7984.2007.00099.x · Cited by 244 · see citing works
Data-based Decision Making: An Overview
Lai, M. K., & Schildkamp, K. (2013) · Data-based Decision Making in Education · doi:10.1007/978-94-007-4816-3_2 · Cited by 167 · see citing works
Staman, L., Visscher, A. J., & Luyten, H. (2014) · Studies in Educational Evaluation · doi:10.1016/j.stueduc.2013.11.002 · Cited by 56 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 14
- Carlson, D., Borman, G. D., & Robinson, M. (2011). A multi-state district-level cluster randomized trial of the impact of data-driven reform on reading and mathematics achievement. Educational Evaluation and Policy Analysis, 33, 378-398. http://dx.doi. org/10.3102/0162373711412765. · DOI · Paper page
- Dunn, K. E., Airola, D. T., Lo, W. J., & Garrison, M. (2013). Becoming data driven: The influence of teachers' sense of efficacy on concerns related to data-driven decision making. The Journal of Experimental Education, 81(2), 222-241. http://dx.doi.org/10. 1080/00220973.2012.699899. · DOI
- Faber, J. M., & Visscher, A. J. (2014). Digitale leerlingvolgsystemen. Een review van de ef- fecten op de leerprestatie [Digital Student monitoring systems: A review of the effects on student performance]. Enschede: Universiteit Twente (commissioned by Kennisnet). Retrieved, April 25, 2014, from: http://www.kennisnet.nl/onderzoek/nieuws/ digitale-leerlingvolgsystemen-een-review-van-de-effecten-opleerprestaties.
- Fullan, M. (2007). The new meaning of educational change. New York and London: Teacher College Press.
- Garet, M. S., Porter, A. C., Desimone, L. M., Birman, B. F., & Yoon, K. S. (2001). What makes professional development effective? Results from a national sample of tea- chers. American Educational Research Journal, 38(4), 915-945. http://dx.doi.org/10. 3102/00028312038004915. · DOI · Paper page
- Hedges, L. V. (2007). Effect sizes in cluster-randomized designs. Journal of Educational and Behavioral Statistics, 32(4), 341-370.
- Ikemoto, G. S., & Marsh, J. A. (2007). Cutting through the "data-driven" mantra: Different conceptions of data-driven decision making. In P. A. Moss (Vol. Ed.), Evidence and decision making. Vol. 106, (pp. 105-131). Malden, MA: Blackwell Publishing Inc.
- Mandinach, E. B., & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Reseacher, 42(1), 30-37. http://dx.doi.org/10. 3102/0013189X12459803. · DOI · Paper page
- McCaffrey, D. F., & Hamilton, L. S. (2007). Value-added assessment in practice: Lessons from the pennsylvania value-added assessment system pilot program, Vol. 506. Rand Corporation.
- Slavin, R. E., Cheung, A., Holmes, G. C., Madden, N. A., & Chamberlain, A. (2013). Effects of a data-driven district reform model on state assessment outcomes. American Educational Research Journal, 50, 371-396.
- Supovitz, J. A., & Turner, H. M. (2000). The effect of professional development on teaching practices and classroom culture. Journal of Research in Science Teaching, 37, 963-980.
- Van Merrienboer, J. J. G., & Kirschner, P. (2013). Ten steps to complex learning. A sys- tematic approach to four-component instructional design. Routledge: New York, London.
- Visscher, A., Peters, M., & Staman, L. (2010). Het Focus-project: Opbrengstgericht werken op basis van prestatiefeedback [The Focus project: Data-based decision making based on performance feedback]. Reken-wiskundeonderwijs: Onderzoek, ontwikkeling, praktijk, Vol. 29, 55-60.
- Wohlstetter, P., Datnow, A., & Park, V. (2008). Creating a system for data-driven decision- making: Applying the principal-agent framework. School Effectiveness and School Improvement, 19, 239-259. http://dx.doi.org/10.1080/09243450802246376. · DOI · Paper page
Cited by
Sorted by citations
Dimensions of teachers’ data literacy: A systematic review of literature from 1990 to 2021
Lee, J., Alonzo, D., Beswick, K., Abril, J. M. V., Chew, A. W., & Oo, C. Z. (2024) · Educational Assessment, Evaluation and Accountability · doi:10.1007/s11092-024-09435-8 · Cited by 40 · see citing works
Powell, S. R., Lembke, E. S., Ketterlin-Geller, L. R., Petscher, Y., Hwang, J., Bos, S. E., Cox, T., Hirt, S., Mason, E. N., Pruitt-Britton, T., et al. (2021) · Studies in Educational Evaluation · doi:10.1016/j.stueduc.2020.100897 · Cited by 37 · see citing works
Albiladi, W., Lasater, K., & Bengtson, E. (2020) · Journal of School Administration Research and Development · doi:10.32674/jsard.v5i2.2240 · Cited by 12 · see citing works
- Authors
- Staman, L. (., Timmermans, A. C. (., & Visscher, A. J. (.
- Affiliations
- University of Twente (NL)
- University of Groningen (NL)
- Corresponding author
- Staman, L. (Laura)
- Venue
- Studies in Educational Evaluation
- Publisher
- Elsevier BV
- Published
- 2017-12
- Volume
- 55
- Pages
- 58-67
- ISSN
- 0191-491X (ISSN-L)
- OpenAlex
- W2732567929
- Cited by
- 38
- References
- 4
- Citations by year
- 2025: 7 · 2024: 4 · 2023: 3 · 2022: 7 · 2021: 3 · 2020: 7 · 2019: 3 · 2018: 4
- FWCI
- 5.82
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Studies In Educational Evaluation (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, other-oa)
- University of Twente Research Information (submittedVersion, other-oa)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Topics
- Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
- Social Sciences › Education › Student Assessment and Feedback
- Social Sciences › Education › Teacher Education and Leadership Studies
- Keywords
- data-driven decision making, academic performance, interim assessment, adaptive instruction, teacher professionalization, academic coaching, prior achievement, socioeconomic status, teacher professional development
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
