The DOI matches its Crossref record; 40 of the 41 references it cites were found in a registry or an index.
Computational thinking and mathematics using Scratch: an experiment with sixth-grade students
Open accessAbstract
The potential benefits from the introduction of programming environments such as Scratch for learning mathematics has reactivated research in this area. Nonetheless, there are few studies which attempt to analyse their influence at the stage of Primary Education. We present the results of a quasi-experimental piece of research with sixth-grade students which studies the influence of Scratch both on the acquisition of mathematical concepts, and on the development of computational thinking. The experiment consisted of two different phases, a programming phase linked to the instruction in Scratch and focused on the acquisition of basic concepts of computational thinking (sequences, iterations, conditionals, and events-handling), and a mathematical phase completely oriented towards the resolution of mathematical tasks. In particular, the mathematical phase focused on word problems whose resolution involves the use of the least common multiple and the greatest common divisor. In order to evaluate the aims of the study, results from tests before and after instruction, both in computational thinking and in the mathematical standards, were compared. The results seem to indicate that Scratch can be used to develop both students’ mathematical ideas and computational thinking.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“As discussed in [53], a visual programming practice can be expressed as the understanding of a single block and the effects that block combinations can produce.”
From ChatScratch: An AI-Augmented System Toward Autonomous Visual Programming Learning for Children Aged 6-12 (2024) · cites this paper as [53]
Citations
Cites
Statistical Power Analysis for the Behavioral Sciences
Muller, K. E., & Cohen, J. (1989) · Technometrics · doi:10.2307/1270020 · Cited by 99,603
Statistical power analysis for the behavioral sciences
Cohen, J. (1990) · Computers Environment and Urban Systems · doi:10.1016/0198-9715(90)90050-4 · Cited by 65,417
(1980) · Medical Entomology and Zoology · Cited by 7,534
Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., Millner, A., Rosenbaum, E., Silver, J., Silverman, B., et al. (2009) · Communications of the ACM · doi:10.1145/1592761.1592779 · Cited by 3,333
Defining Computational Thinking for Mathematics and Science Classrooms
Weintrop, D., Beheshti, E., Horn, M., Orton, K., Jona, K., Trouille, L. E., & Wilensky, U. J. (2015) · Journal of Science Education and Technology · doi:10.1007/s10956-015-9581-5 · Cited by 1,974
Computational thinking and thinking about computing
Wing, J. M. (2008) · Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences · doi:10.1098/rsta.2008.0118 · Cited by 1,784
Demystifying computational thinking
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017) · Educational Research Review · doi:10.1016/j.edurev.2017.09.003 · Cited by 1,466
Lye, S. Y., & Koh, J. H. L. (2014) · Computers in Human Behavior · doi:10.1016/j.chb.2014.09.012 · Cited by 1,421
Román-González, ., Pérez-González, J. C., & Fernández, C. J. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.08.047 · Cited by 867
Changing minds: computers, learning, and literacy
(2001) · Choice Reviews Online · doi:10.5860/choice.38-2855 · Cited by 813
Research works printed but not linked: 3
- González-Calero J. A., 2016, Investigación en Educación Matemática XX, 295
- Noblet K., 2013, Proceedings of the 16th annual conference on research in undergraduate mathematics education, 219
- Seehorn D., 2011, CSTA k–12 computer science standards: Revised 2011
Cited by
Sorted by citations
Assessing computational thinking: A systematic review of empirical studies
Tang, X., Yin, Y., Lin, Q., Hadad, R., & Zhai, X. (2020) · Computers & Education · doi:10.1016/j.compedu.2019.103798 · Cited by 647
Ye, H., Liang, B., Ng, O., & Chai, C. S. (2023) · International Journal of STEM Education · doi:10.1186/s40594-023-00396-w · Cited by 311
Empirical research on problem solving and problem posing: a look at the state of the art
Liljedahl, P., & Cai, J. (2021) · ZDM · doi:10.1007/s11858-021-01291-w · Cited by 138
Zhao, L., Liu, X., Wang, C., & Su, Y.-S. (2022) · Computers & Education · doi:10.1016/j.compedu.2022.104445 · Cited by 109
Cheng, Y.-P., Lai, C.-F., Chen, Y.-T., Wang, W.-S., Huang, Y.-M., & Wu, T.-T. (2023) · Computers & Education · doi:10.1016/j.compedu.2023.104794 · Cited by 130
Metadata
- Authors
- Rodríguez-Martínez, J. A., González-Calero, J. A., & Sáez-López, J. M.
- Affiliations
- Department of Mathematics, School of Education of Albacete (Edificio Simón Abril), University of Castilla-La Mancha, Albacete, Spain
- Departament de Didactics, Faculty of Education, Spanish National University of Distance Education (UNED), Madrid, Spain
- Venue
- Interactive Learning Environments
- Publisher
- Informa UK Limited
- Published
- 2019-05-02
- Volume
- 28
- Issue
- 3
- Pages
- 316-327
- ISSN
- 1049-4820 (ISSN-L)
- 1744-5191
- OpenAlex
- W2943780196
- Cited by
- 214
- References
- 41
- Citations by year
- 2026: 29 · 2025: 22 · 2024: 40 · 2023: 56 · 2022: 30 · 2021: 21 · 2020: 15 · 2019: 1
- FWCI
- 18.13
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- other-oa
- Locations
- Interactive Learning Environments (publishedVersion)
- UNED repository (submittedVersion, other-oa)
- RUIdeRA - Institutional University Repository (University of Castilla-La Mancha) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Social Sciences › Education › Mathematics Education and Teaching Techniques
- Social Sciences › Education › Mathematics Education and Pedagogy
- Keywords
- computational thinking, Scratch, mathematics education, sixth grade students, word problems, least common multiple, greatest common divisor
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
