Cited by 24Behavioral and Psychological StudiesReading and Literacy DevelopmentEducational Assessment and Improvement

An Analysis of Consistency Between Team Decisions and Reading Assessment Data Within an RTI Model

Shapiro, Edward S., Hilt-Panahon, Alexandra, Gischlar, Karen L., Semeniak, Kathleen, Leichman, Erin, Bowles, Shelly·2012·Remedial and Special Education

Abstract

Data-based decision making by teams is central to implementation of response to intervention (RTI) models. Few studies have examined the actual decision-making process within RTI systems of service delivery. The purpose of this study was to examine the tier assignment decisions for students across grade-level teams in three K–5 elementary schools implementing identical RTI models for reading. Decisions of grade-level teams primarily composed of teachers were compared against the recommendation made by the Dynamic Indicators of Basic Early Literacy Skills (DIBELS) universal screening measure during fall and winter assessments across a 2-year period. Results showed teams had high overall levels of agreement with the DIBELS recommendations, especially after Grade 1 and during the winter of each year. When teams initially disagreed with the DIBELS recommendations, increased agreement in the use of data-based decisions was present over time. Implications for the data decision-making process within an RTI model are discussed.

Integrity signals

Registry

Crossref · 10.1177/0741932510397763

Cites

1 of 1 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?

  • When decision making teams use multiple pieces of data (i.e., universal screening data, CBM, in-class assessments), they increase decision accuracy.

    “When decision making teams use multiple pieces of data (i.e., universal screening data, CBM, in-class assessments), they increase decision accuracy [45].”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Shapiro, E. S., Hilt-Panahon, A., Gischlar, K. L., Semeniak, K., Leichman, E., & Bowles, S.
Affiliations
  • Lehigh University (US)
  • Minnesota State University, Mankato, Mankato, MN, USA
  • Rider University (US)
  • Child Care Associates, Fort Worth, TX, USA
Venue
Remedial and Special Education
Published
2011-02-18
Volume
33
Issue
6
Pages
335-347
ISSN
  • 0741-9325 (ISSN-L)
  • 1538-4756
OpenAlex
W2169619660
Cited by
24
References
1
Citations by year
2024: 1 · 2022: 1 · 2021: 1 · 2020: 2 · 2019: 1 · 2017: 3 · 2016: 4 · 2015: 5 · 2014: 2 · 2013: 1 · 2012: 3
FWCI
3.94
Type
journal article
Language
en
Open access
closed
Locations
Remedial and Special Education (publishedVersion)
Topics
  • Social Sciences › Psychology › Developmental and Educational Psychology › Behavioral and Psychological Studies
  • Social Sciences › Psychology › Developmental and Educational Psychology › Reading and Literacy Development
  • Social Sciences › Decision Sciences › Information Systems and Management › Educational Assessment and Improvement
Keywords
Response to Intervention, data-driven decision making, team decision-making, DIBELS, universal screening, reading assessment, early literacy, elementary school, K-5 students, decision consistency, teacher teams

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