Cited by 94Motivation and Self-Concept in SportsExperimental Behavioral Economics StudiesEducation, Achievement, and Giftedness

Increasing and decreasing intrinsic interest with contingent rewards: A test of cognitive evaluation theory

Enzle, Michael E, Ross, June M·1978·Journal of Experimental Social Psychology

Integrity signals

Registry

Crossref · 10.1016/0022-1031(78)90052-5

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  • The usual finding is that rewards given regardless of quality of performance tend to reduce interest, whereas rewards for performances signifying competence sustain high interest.

    “Although results are somewhat variable, the usual finding is that rewards given regardless of quality of performance tend to reduce interest, whereas rewards for performances signifying competence sustain high interest (Boggiano & Ruble, 1979;Enzle & Ross, 1978;Lepper & Greene, 1979;Ross, 1976).”

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References 16 · Cited by 94

Authors
Enzle, M. E., & Ross, J. M.
Affiliations
University of Alberta (CA)
Corresponding author
Enzle, Michael E
Venue
Journal of Experimental Social Psychology
Publisher
Elsevier BV
Published
1978-11
Volume
14
Issue
6
Pages
588-597
ISSN
0022-1031 (ISSN-L)
OpenAlex
W2043589836
Cited by
94
References
16
Citations by year
2024: 1 · 2023: 2 · 2022: 2 · 2021: 2 · 2020: 1 · 2018: 1 · 2017: 5 · 2016: 4 · 2014: 3 · 2013: 1 · 2012: 3
FWCI
7.34
Type
journal article
Language
en
Open access
closed
Locations
Journal of Experimental Social Psychology (publishedVersion)
Topics
  • Social Sciences › Psychology › Social Psychology › Motivation and Self-Concept in Sports
  • Social Sciences › Safety Research › Experimental Behavioral Economics Studies
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
Keywords
intrinsic motivation, contingent reward, cognitive evaluation theory, task interest, reward value, performance standards, extrinsic motivation

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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.

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