What happens when university students try to answer prequestions that accompany textbook material
Integrity 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?
Pretesting enhances subsequent learning by activating prior knowledge, revealing knowledge gaps, and sharpening attention to critical information encountered later.
“a substantial body of research demonstrates that pretesting enhances subsequent learning by activating prior knowledge, revealing knowledge gaps, and sharpening attention to critical information encountered later [2, 9, 11-13].”
From Do Gains from Generative AI-Enabled Adaptive Pretesting Persist? Evidence from a Retention Study (2026) · cites this paper as [12]
The citation lists haven’t been fetched yet
References 22 · Cited by 71
- Authors
- Pressley, M., Tanenbaum, R., McDaniel, M. A., & Wood, E.
- Affiliations
- Western University (CA)
- Purdue University West Lafayette (US)
- Corresponding author
- Pressley, Michael
- Venue
- Contemporary Educational Psychology
- Publisher
- Elsevier BV
- Published
- 1990-01
- Volume
- 15
- Issue
- 1
- Pages
- 27-35
- ISSN
- 0361-476X (ISSN-L)
- OpenAlex
- W2037141737
- Cited by
- 71
- References
- 22
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 1 · 2023: 5 · 2022: 2 · 2021: 4 · 2020: 6 · 2019: 9 · 2018: 2 · 2017: 3 · 2016: 3 · 2014: 4 · 2013: 5 · 2012: 2
- FWCI
- 0.24
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Contemporary Educational Psychology (publishedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Strategies and Epistemologies
- Keywords
- prior knowledge activation, reading textbooks, reading comprehension, memory retrieval, university students, learning from reading
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.
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