Cited by 201Gender and Technology in EducationDigital literacy in educationTechnology Adoption and User Behaviour

Computer technologies: Attitudes and self-efficacy across undergraduate disciplines

Kinzie, Mable B., Delcourt, Marcia A. B., Powers, Susan M.·1994·Research in Higher Education

Integrity signals

Registry

Crossref · 10.1007/bf02497085

Cites

37 of 37 references verified0 citation errors · 0 not checkable

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Claims the paper makes

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  • University students' self-efficacy regarding computer use is positively associated with their attitudes towards computers.

    “Studies to date suggest that university students' self-efficacy regarding computer use is positively associated with their attitudes towards computers (Kinzie, Delcourt, & Powers, 1994)”

    From Factors Affecting Students' Attitudes toward Computer Programming (2019) · cites this paper as Kinzie, Delcourt, & Powers, 1994

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Authors
Kinzie, M. B., Delcourt, M. A. B., & Powers, S. M.
Affiliations
  • University of Virginia (US)
  • McGill University (CA)
Venue
Research in Higher Education
Published
1994-11
Volume
35
Issue
6
Pages
745-768
ISSN
  • 0361-0365 (ISSN-L)
  • 1573-188X
OpenAlex
W2013022160
Cited by
199
References
39
Citations by year
2026: 1 · 2025: 4 · 2024: 2 · 2023: 4 · 2022: 5 · 2021: 7 · 2020: 6 · 2019: 3 · 2018: 7 · 2017: 7 · 2016: 6 · 2015: 9 · 2014: 6 · 2013: 11 · 2012: 13
FWCI
6.98
Type
journal article
Language
en
Open access
closed
Locations
Research in Higher Education (publishedVersion)
Topics
  • Social Sciences › Gender Studies › Gender and Technology in Education
  • Physical Sciences › Computer Science › Information Systems › Digital literacy in education
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Keywords
self-efficacy, undergraduate students, perceived usefulness, computer anxiety, word processing, email, spreadsheet software, database applications, statistical software, CD-ROM databases, business students, pedagogy students, nursing students, predictors of self-efficacy

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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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