Adolescents' computer performance: The role of self-concept and motivational aspects
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Boys performed significantly better than girls on scales that required more technical knowledge (e.g., basic operations, information networks, programming, and database operations).
“While boys performed significantly better than girls on scales that required more technical knowledge (e.g., basic operations, information networks, programming, and database operations; Aesaert & van Braak, 2015;Christoph, Goldhammer, Zylka, & Hartig, 2015;Lau & Yuen, 2014;Meri-Tuulia et al., 2017).”
From Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy (2019) · cites this paper as Christoph et al., 2015
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References 46 · Cited by 77
- Authors
- Christoph, G., Goldhammer, F., Zylka, J., & Hartig, J.
- Affiliations
- DIPF | Leibniz Institute for Research and Information in Education (DE)
- Corresponding author
- Christoph, Gabriela
- Venue
- Computers & Education
- Publisher
- Elsevier BV
- Published
- 2015-02
- Volume
- 81
- Pages
- 1-12
- ISSN
- 0360-1315 (ISSN-L)
- OpenAlex
- W2062152087
- Cited by
- 77
- References
- 46
- Citations by year
- 2026: 8 · 2025: 5 · 2024: 2 · 2023: 5 · 2022: 14 · 2021: 6 · 2020: 9 · 2019: 3 · 2018: 6 · 2017: 7 · 2016: 8 · 2015: 4
- FWCI
- 16.12
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers & Education (publishedVersion)
- Topics
- Social Sciences › Gender Studies › Gender and Technology in Education
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
- Physical Sciences › Computer Science › Information Systems › Digital literacy in education
- Keywords
- adolescents, computer performance, computer basics, motivation, expectancy-value theory, gender differences, high school students
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.
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