Cited by 56Psychometric Methodologies and TestingStudent Assessment and FeedbackEducational Technology and Assessment

The influence of test familiarity and student disability status upon teachers' judgments of students' test performance

Hurwitz, Jason T., Elliott, Stephen N., Braden, Jeffery P.·2007·School Psychology Quarterly

Integrity signals

Registry

Crossref · 10.1037/1045-3830.22.2.115

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

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Claims other papers make about this one

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  • Current research indicates group-specific biases in teacher expectations.

    “A central challenge in the implementation of high expectations for all students, however, may be to reduce biasing influences associated with students' gender, family backgrounds and disabilities, as current research indicates group-specific biases in teacher expectations (e.g., Hurwitz et al., 2007; Lorenz et al., 2016).”

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References 9 · Cited by 56

Authors
Hurwitz, J. T., Elliott, S. N., & Braden, J. P.
Affiliations
  • University of Wisconsin–Madison (US)
  • Vanderbilt University (US)
  • North Carolina State University (US)
Venue
School Psychology Quarterly
Published
2007-06
Volume
22
Issue
2
Pages
115-144
ISSN
  • 1045-3830 (ISSN-L)
  • 1939-1560
OpenAlex
W1963936957
Cited by
56
References
9
Citations by year
2026: 1 · 2025: 1 · 2024: 3 · 2023: 3 · 2022: 7 · 2021: 3 · 2020: 2 · 2019: 5 · 2018: 4 · 2017: 3 · 2016: 4 · 2015: 3 · 2014: 3 · 2013: 3 · 2012: 1
FWCI
2.87
Type
journal article
Language
en
Open access
closed
Locations
School Psychology Quarterly (publishedVersion)
Topics
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Social Sciences › Education › Student Assessment and Feedback
  • Physical Sciences › Computer Science › Information Systems › Educational Technology and Assessment
Keywords
test familiarity, student disability, test performance, teacher ratings, students with disabilities

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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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