Scratch: programming for all
Abstract
"Digital fluency" should mean designing, creating, and remixing, not just browsing, chatting, and interacting.
Integrity signals
Registry
Cites
Statistics
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?
Scratch integrates coding into the everyday creative activities of children, incorporating storytelling, drawing, and gaming as fundamental forms of expression.
“In discussing Scratch, it extends beyond the traditional view of programming as merely a coding skill. Instead, Scratch integrates coding into the everyday creative activities of children, incorporating storytelling, drawing, and gaming as fundamental forms of expression [51].”
From ChatScratch: An AI-Augmented System Toward Autonomous Visual Programming Learning for Children Aged 6-12 (2024) · cites this paper as [51]
Autonomous learning without the structured guidance of a classroom is often less effective.
“Although these students can, in theory, avail themselves of publicly available resources online, research shows that autonomous learning without the structured guidance of a classroom is often less effective [14, 39, 51].”
From ChatScratch: An AI-Augmented System Toward Autonomous Visual Programming Learning for Children Aged 6-12 (2024) · cites this paper as [51]
For children without access to educational resources or guidance from educators, learning within paradigms without classroom support is often ineffective.
“Moreover, for children without access to educational resources or guidance from educators, learning within paradigms without classroom support is often ineffective [14, 39, 51].”
From ChatScratch: An AI-Augmented System Toward Autonomous Visual Programming Learning for Children Aged 6-12 (2024) · cites this paper as [51]
Scratch remains the most commonly used platform in children's programming education.
“While there are numerous alternatives, Scratch remains the most commonly used platform in children's programming education, primarily because of its inherent tinkerable nature, profound meaningfulness, and vibrant social community [51].”
From ChatScratch: An AI-Augmented System Toward Autonomous Visual Programming Learning for Children Aged 6-12 (2024) · cites this paper as [51]
Personally meaningful projects align exceptionally well with Scratch in autonomous learning environments.
“Personally meaningful projects, which allow children to freely choose their themes and forms of implementation, align exceptionally well with Scratch [51] in autonomous learning environments [14].”
From ChatScratch: An AI-Augmented System Toward Autonomous Visual Programming Learning for Children Aged 6-12 (2024) · cites this paper as [51]
Scratch projects require a phase of creative thinking and conceptualization before one starts coding.
“In contrast, Scratch projects require a phase of creative thinking and conceptualization before one starts coding [51].”
From ChatScratch: An AI-Augmented System Toward Autonomous Visual Programming Learning for Children Aged 6-12 (2024) · cites this paper as [51]
Cited by
Sorted by citations
What is AI Literacy? Competencies and Design Considerations
Long, D., & Magerko, B. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376727 · Cited by 3,241 · see citing works
Competition-level code generation with AlphaCode
Li, Y., Choi, D., Chung, J., Kushman, N., Schrittwieser, J., Leblond, R., Eccles, T., Keeling, J., Gimeno, F., Dal Lago, A., et al. (2022) · Science · doi:10.1126/science.abq1158 · Cited by 1,043 · see citing works
Students’ Misconceptions and Other Difficulties in Introductory Programming: A Literature Review
Qian, Y., & Lehman, J. (2018) · ACM Transactions on Computing Education · doi:10.1145/3077618 · Cited by 529 · see citing works
A Systematic Review of Studies on Educational Robotics
Anwar, S., Bascou, N. A., Menekse, M., & Kardgar, A. (2019) · Journal of Pre-College Engineering Education Research (J-PEER) · doi:10.7771/2157-9288.1223 · Cited by 419 · see citing works
The Robots Are Here: Navigating the Generative AI Revolution in Computing Education
Prather, J., Denny, P., Leinonen, J., Becker, B. A., Albluwi, I., Craig, M., Keuning, H., Kiesler, N., Kohn, T., Luxton-Reilly, A., et al. (2023) · Proceedings of the 2023 Working Group Reports on Innovation and Technology in Computer Science Education · doi:10.1145/3623762.3633499 · Cited by 396 · see citing works
Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming
Kazemitabaar, M., Chow, J., Ma, C. K. T., Ericson, B. J., Weintrop, D., & Grossman, T. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580919 · Cited by 366 · see citing works
Empirical studies on the Maker Movement, a promising approach to learning: A literature review
Papavlasopoulou, S., Giannakos, M. N., & Jaccheri, L. (2017) · Entertainment Computing · doi:10.1016/j.entcom.2016.09.002 · Cited by 317 · see citing works
An Empirical Investigation into Programming Language Syntax
Stefik, A., & Siebert, S. (2013) · ACM Transactions on Computing Education · doi:10.1145/2534973 · Cited by 295 · see citing works
Programming, Problem Solving, and Self-Awareness: Effects of Explicit Guidance
Loksa, D., Ko, A. J., Jernigan, W., Oleson, A., Mendez, C. J., & Burnett, M. M. (2016) · Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858252 · Cited by 223 · see citing works
Computational thinking and mathematics using Scratch: an experiment with sixth-grade students
Rodríguez-Martínez, J. A., González-Calero, J. A., & Sáez-López, J. M. (2020) · Interactive Learning Environments · doi:10.1080/10494820.2019.1612448 · Cited by 214 · see citing works
Habits of programming in scratch
Meerbaum-Salant, O., Armoni, M., & Ben-Ari, M. (2011) · Proceedings of the 16th annual joint conference on Innovation and technology in computer science education · doi:10.1145/1999747.1999796 · Cited by 199 · see citing works
Weintrop, D., & Wilensky, U. (2015) · Proceedings of the eleventh annual International Conference on International Computing Education Research · doi:10.1145/2787622.2787721 · Cited by 198 · see citing works
Developing Computational Thinking with Educational Technologies for Young Learners
Ching, Y.-H., Hsu, Y.-C., & Baldwin, S. (2018) · TechTrends · doi:10.1007/s11528-018-0292-7 · Cited by 202 · see citing works
Dr. Scratch: a Web Tool to Automatically Evaluate Scratch Projects
Moreno-León, J., & Robles, G. (2015) · Proceedings of the Workshop in Primary and Secondary Computing Education · doi:10.1145/2818314.2818338 · Cited by 183 · see citing works
Intelligent tutoring systems for programming education: a systematic review
Crow, T., Luxton-Reilly, A., & Wuensche, B. (2018) · Proceedings of the 20th Australasian Computing Education Conference · doi:10.1145/3160489.3160492 · Cited by 166 · see citing works
A differentiated discussion about AI education K-12
Steinbauer, G., Kandlhofer, M., Chklovski, T., Heintz, F., & Koenig, S. (2021) · KI - Künstliche Intelligenz · doi:10.1007/s13218-021-00724-8 · Cited by 160 · see citing works
Margulieux, L. E., Guzdial, M., & Catrambone, R. (2012) · Proceedings of the ninth annual international conference on International computing education research · doi:10.1145/2361276.2361291 · Cited by 149 · see citing works
From Gaming to Computational Thinking: An Adaptive Educational Computer Game-Based Learning Approach
Hooshyar, D., Pedaste, M., Yang, Y., Malva, L., Hwang, G.-J., Wang, M., Lim, H., & Delev, D. (2021) · Journal of Educational Computing Research · doi:10.1177/0735633120965919 · Cited by 132 · see citing works
Co-designing AI literacy exhibits for informal learning spaces
Long, D., Blunt, T., & Magerko, B. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3476034 · Cited by 128 · see citing works
MIT App Inventor: Objectives, Design, and Development
Patton, E. W., Tissenbaum, M., & Harunani, F. (2019) · Computational Thinking Education · doi:10.1007/978-981-13-6528-7_3 · Cited by 121 · see citing works
Focusing on Teacher Education to Introduce AI in Schools: Perspectives and Illustrative Findings
Vazhayil, A., Shetty, R., Bhavani, R. R., & Akshay, N. (2019) · 2019 IEEE Tenth International Conference on Technology for Education (T4E) · doi:10.1109/t4e.2019.00021 · Cited by 131 · see citing works
Assessing learning in technology-rich maker activities: A systematic review of empirical research
Lin, Q., Yin, Y., Tang, X., Hadad, R., & Zhai, X. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103944 · Cited by 90 · see citing works
Bauer, C. C. C., Caballero, C., Scherer, E., West, M. R., Mrazek, M. D., Phillips, D. T., Whitfield-Gabrieli, S., & Gabrieli, J. D. E. (2019) · Behavioral Neuroscience · doi:10.1037/bne0000337 · Cited by 85 · see citing works
Dietz, G., Le, J. K., Tamer, N., Han, J., Gweon, H., Murnane, E. L., & Landay, J. A. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445039 · Cited by 67 · see citing works
Digital game-based language learning for vocabulary development
Chowdhury, M., Dixon, L., Kuo, L.-J., Donaldson, J. P., Eslami, Z., Viruru, R., & Luo, W. (2024) · Computers and Education Open · doi:10.1016/j.caeo.2024.100160 · Cited by 64 · see citing works
Uncovering Trajectories of Informal Learning in Large Online Communities of Creators
Yang, S., Domeniconi, C., Revelle, M., Sweeney, M., Gelman, B. U., Beckley, C., & Johri, A. (2015) · Proceedings of the Second (2015) ACM Conference on Learning @ Scale · doi:10.1145/2724660.2724674 · Cited by 60 · see citing works
Supporting Diverse and Creative Collaboration in the Scratch Online Community
Roque, R., Rusk, N., & Resnick, M. (2016) · Mass Collaboration and Education · doi:10.1007/978-3-319-13536-6_12 · Cited by 57 · see citing works
Self-citationChen, L., Xiao, S., Chen, Y., Song, Y., Wu, R., & Sun, L. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642229 · Cited by 60 · see citing works
Dangol, A., Newman, M., Wolfe, R., Lee, J. H., Kientz, J. A., Yip, J., & Pitt, C. (2024) · Designing Interactive Systems Conference · doi:10.1145/3643834.3661515 · Cited by 42 · see citing works
Factors Affecting Students' Attitudes toward Computer Programming
Derya GURER, M., CETIN, I., & TOP, E. (2019) · Informatics in Education · doi:10.15388/infedu.2019.13 · Cited by 37 · see citing works
TurtleTalk: An Educational Programming Game for Children with Voice User Interface
Jung, H., Kim, H. J., So, S., Kim, J., & Oh, C. (2019) · Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290607.3312773 · Cited by 33 · see citing works
Decoding Debugging Instruction: A Systematic Literature Review of Debugging Interventions
Yang, S., Baird, M., O’Rourke, E., Brennan, K., & Schneider, B. (2024) · ACM Transactions on Computing Education · doi:10.1145/3690652 · Cited by 29 · see citing works
Self-citationExploring AR and VR Tools in Mathematics Education Through Culturally Responsive Pedagogies
Bertrand, M. G., Sezer, H. B., & Namukasa, I. K. (2024) · Digital Experiences in Mathematics Education · doi:10.1007/s40751-024-00152-x · Cited by 28 · see citing works
Visual StoryCoder: A Multimodal Programming Environment for Children’s Creation of Stories
Dietz, G., Tamer, N., Ly, C., Le, J. K., & Landay, J. A. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580981 · Cited by 24 · see citing works
Roque, R., Tamashiro, M. A., Mcconnell, K., & Granados, J. (2021) · Interaction Design and Children · doi:10.1145/3459990.3460728 · Cited by 20 · see citing works
Santos, P., El Aadmi, K., Calvera-Isabal, M., & Rodríguez, A. (2025) · International Journal of Technology and Design Education · doi:10.1007/s10798-025-10001-6 · Cited by 15 · see citing works
“%) had previous experience using Scratch, followed by 31.13% using Beebot and 28.30% with Makey Makey.”
InfluentialKimmerle, J., Moskaliuk, J., Brendle, D., & Cress, U. (2017) · International Journal of Computer-Supported Collaborative Learning · doi:10.1007/s11412-017-9258-6 · Cited by 12 · see citing works
Computing Education Research Today
Fincher, S. A., Tenenberg, J., Dorn, B., Hundhausen, C., McCartney, R., & Murphy, L. (2019) · The Cambridge Handbook of Computing Education Research · doi:10.1017/9781108654555.003 · Cited by 7 · see citing works
- Authors
- Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., Millner, A., Rosenbaum, E., Silver, J., Silverman, B., & Kafai, Y.
- Affiliations
- Massachusetts Institute of Technology (US)
- Massachusetts Institute of Technology, Cambridge, MA
- Playful Invention Company, Montreal, Quebec, Canada
- University of Pennsylvania (US)
- Venue
- Communications of the ACM
- Published
- 2009-11
- Volume
- 52
- Issue
- 11
- Pages
- 60-67
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2084944215
- Cited by
- 3,333
- References
- 0
- Citations by year
- 2026: 195 · 2025: 207 · 2024: 234 · 2023: 239 · 2022: 197 · 2021: 275 · 2020: 250 · 2019: 326 · 2018: 226 · 2017: 246 · 2016: 203 · 2015: 219 · 2014: 173 · 2013: 113 · 2012: 108
- FWCI
- 1517.31
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Communications of the ACM (publishedVersion)
- Funders
- National Science Foundation
- Topics
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Literacy, Media, and Education
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Computer Science › Information Systems › Digital literacy in education
- Keywords
- Scratch, digital fluency, remix, digital creation, programming education
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
