Rubrics: Tools for Making Learning Goals and Evaluation Criteria Explicit for Both Teachers and Learners
Open accessIntegrity 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?
The use of rubrics can help remove bias from grading (Allen and Tanner, 2006) by increasing grading consistency.
“The use of rubrics can also help remove bias from grading (Allen and Tanner, 2006) by increasing grading consistency.”
From Teaching More by Grading Less (or Differently) (2014) · cites this paper as Allen and Tanner, 2006
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References 15 · Cited by 314
- Authors
- Allen, D., & Tanner, K.
- Affiliations
- University of Delaware (US)
- San Francisco State University (US)
- ORCID
- Allen, Deborah
- Venue
- CBE—Life Sciences Education
- Published
- 2006-09
- Volume
- 5
- Issue
- 3
- Pages
- 197-203
- ISSN
- 1931-7913 (ISSN-L)
- OpenAlex
- W2104386136
- Cited by
- 314
- References
- 15
- Citations by year
- 2026: 24 · 2025: 17 · 2024: 28 · 2023: 27 · 2022: 18 · 2021: 20 · 2020: 26 · 2019: 22 · 2018: 15 · 2017: 14 · 2016: 14 · 2015: 37 · 2014: 15 · 2013: 5 · 2012: 6
- FWCI
- 16.15
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- CBE—Life Sciences Education (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Division of Mathematical Sciences
- Topics
- Social Sciences › Education › Student Assessment and Feedback
- Social Sciences › Education › Educational Assessment and Pedagogy
- Social Sciences › Education › Evaluation of Teaching Practices
- Keywords
- rubrics, learning objectives, evaluation criteria, learning outcomes, teacher-student communication, life sciences education
- MeSH terms
- Educational Measurement, Faculty, Goals, Learning, Students, Models, Educational
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.
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