Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 518

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Virtually Perfect Time Sharing in Dual-Task Performance: Uncorking the Central Cognitive Bottleneck

Schumacher, Eric H., Seymour, Travis L., Glass, Jennifer M., Fencsik, David E., Lauber, Erick J., Kieras, David E., Meyer, David E.·2001·Psychological Science
DOI 10.1111/1467-9280.00318
Open this paper in CoChat — free account

Abstract

A fundamental issue for psychological science concerns the extent to which people can simultaneously perform two perceptual-motor tasks. Some theorists have hypothesized that such dual-task performance is severely and persistently constrained by a central cognitive “bottleneck,” whereas others have hypothesized that skilled procedural decision making and response selection for two or more tasks can proceed at the same time under adaptive executive control. The three experiments reported here support this latter hypothesis. Their results show that after relatively modest amounts of practice, at least some participants achieve virtually perfect time sharing in the dual-task performance of basic choice reaction tasks. The results also show that observed interference between tasks can be modulated by instructions about differential task priorities and personal preferences for daring (concurrent) or cautious (successive) scheduling of tasks. Given this outcome, future research should investigate exactly when and how such sophisticated skills in dual-task performance are acquired.

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 · 10.1111/1467-9280.00318

Cites

2 of 2 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 2 references

Cited by

Metadata

Authors
Schumacher, E. H., Seymour, T. L., Glass, J. M., Fencsik, D. E., Lauber, E. J., Kieras, D. E., & Meyer, D. E.
Venue
Psychological Science
Publisher
SAGE Publications
Published
2001-03
Volume
12
Issue
2
Pages
101-108
ISSN
  • 0956-7976 (ISSN-L)
  • 1467-9280
DOI
10.1111/1467-9280.00318
OpenAlex
W2158753285
Cited by
518
References
2
FWCI
6.68
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.