Cited by 132Teaching and Learning ProgrammingGender and Technology in EducationEducational Robotics and Engineering

Making the Maker: A Means-to-an-Ends approach to nurturing the Maker mindset in elementary-aged children

Open access
Chu, Sharon Lynn, Quek, Francis, Bhangaonkar, Sourabh, Ging, Amy Boettcher, Sridharamurthy, Kumar·2015·International Journal of Child-Computer Interaction

Integrity signals

Registry

Crossref · 10.1016/j.ijcci.2015.08.002

Cites

25 of 25 references verified0 citation errors · 0 not checkable

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Claims the paper makes

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Claims other papers make about this one

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Cites

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1 of the 26 references couldn’t be matched to a known paper.

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Authors
Chu, S. L., Quek, F., Bhangaonkar, S., Ging, A. B., & Sridharamurthy, K.
Affiliations
Texas A&M University (US)
Corresponding author
Chu, Sharon Lynn
Venue
International Journal of Child-Computer Interaction
Publisher
Elsevier BV
Published
2015-09
Volume
5
Pages
11-19
ISSN
2212-8689 (ISSN-L)
OpenAlex
W2195838439
Cited by
132
References
26
Citations by year
2026: 4 · 2025: 10 · 2024: 16 · 2023: 7 · 2022: 14 · 2021: 18 · 2020: 15 · 2019: 18 · 2018: 11 · 2017: 13 · 2016: 5 · 2015: 1
FWCI
15.04
Type
journal article
Language
en
Update notices
erratum (2024-09-01)
Open access
Locations
International Journal of Child-Computer Interaction (acceptedVersion)
Funders
National Science Foundation (CNS-1439614, DRL-1433770)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
  • Social Sciences › Gender Studies › Gender and Technology in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Educational Robotics and Engineering
Keywords
making, maker mindset, maker identity, elementary school students, storytelling, self-efficacy, motivation, interest, STEM education, child-computer interaction

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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.

Statistics and arithmetic are recomputed, not judged.

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