Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 745

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Learning from texts: Effects of prior knowledge and text coherence

McNamara, Danielle S., Kintsch, Walter·1996·Discourse Processes

Abstract

Two experiments, theoretically motivated by the construction‐integration model of comprehension (W. Kintsch, 1988), investigated effects of prior knowledge on learning from high‐ and low‐coherence history texts. In Experiment 1, participants’ comprehension was examined through free recall, multiple‐choice questions, and a keyword sorting task. An advantage was found for the high‐coherence text on recall and multiple‐choice questions. However, high‐knowledge readers performed better on the sorting task after reading the low‐coherence text. In Experiment 2, participants’ comprehension was examined through open‐ended questions and the sorting task both immediately and after a 1‐week delay. Little effect of delay was found, and the previous sorting task results failed to replicate. As predicted, high‐knowledge readers performed better on the open‐ended questions after reading the low‐coherence text. Reading times from both experiments indicated that the low‐coherence text requires more inference processes. These inferences are more likely to be successful and useful for high‐knowledge readers.

Overview

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1080/01638539609544975

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Verification

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.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Cited by

Metadata

Authors
McNamara, D. S., & Kintsch, W.
Venue
Discourse Processes
Published
1996-10
Volume
22
Issue
3
Pages
247-288
ISSN
  • 0163-853X (ISSN-L)
  • 1532-6950
OpenAlex
W2028131103
Cited by
745
References
3
FWCI
10.41
Type
journal article
Language
en
Open access
closed

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

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.