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ScratchLog: Live Learning Analytics for Scratch

Published: 30 June 2023 Publication History

Abstract

Scratch is a hugely popular block-based programming environment that is often used in educational settings, and has therefore recently also become a focus for research on programming education. Scratch provides dedicated teacher accounts that make it easy and convenient to handle lessons with school classes. However, once learners join a Scratch classroom, it is challenging to keep track of what they are doing: Both teachers and researchers may be interested in learning analytics to help them monitor students or evaluate teaching material. Researchers may also be interested in understanding how programs are created and how learners use Scratch. Neither use case is supported by Scratch itself currently. In this paper, we introduce ScratchLog, a tool that collects data from learners using Scratch. ScratchLog provides custom user management and makes it easy to set up courses and assignments. Starting from a task description and a starter project, learners transparently use Scratch while ScratchLog collects usage data, such as the history of code edits, or statistics about how the Scratch user interface was used. This data can be viewed on the ScratchLog web interface, or exported for further analysis, for example to inspect the functionality of programs using automated tests.

References

[1]
Efthimia Aivaloglou, Felienne Hermans, Jesús Moreno-León, and Gregorio Robles. 2017. A dataset of scratch programs: scraped, shaped and scored. In Proceedings of the 14th International Conference on Mining Software Repositories. IEEE, 511--514.
[2]
Ryan S Baker, Taylor Martin, and Lisa M Rossi. 2016. Educational data mining and learning analytics. The Wiley handbook of cognition and assessment: Frameworks, methodologies, and applications (2016), 379--396.
[3]
Bryce Boe, Charlotte Hill, Michelle Len, Greg Dreschler, Phillip Conrad, and Diana Franklin. 2013. Hairball: Lint-inspired static analysis of scratch projects. SIGCSE 2013 - Proceedings of the 44th ACM Technical Symposium on Computer Science Education, 215--220. https://doi.org/10.1145/2445196.2445265
[4]
Doug Clow. 2013. An overview of learning analytics. Teaching in Higher Education, Vol. 18, 6 (2013), 683--695.
[5]
Sayamindu Dasgupta and Benjamin Mako Hill. 2017. Scratch community blocks: Supporting children as data scientists. In Proceedings of the 2017 CHI conference on human factors in computing systems. 3620--3631.
[6]
Benedikt Fein, Isabella Graßl, Florian Beck, and Gordon Fraser. 2022. An Evaluation of code2vec Embeddings for Scratch. (2022).
[7]
Cassia Fernandez, Jo ao Adriano Freitas, Roseli de Deus Lopes, and Paulo Blikstein. 2022. Using video analysis and learning analytics to understand programming trajectories in data science activities with Scratch. In Interaction Design and Children. 253--260.
[8]
Daniel Amo Filvà, Marc Alier Forment, Francisco José Garc'ia-Pe nalvo, David Fonseca Escudero, and Mar'ia José Casa n. 2019. Clickstream for learning analytics to assess students' behavior with Scratch. Future Generation Computer Systems, Vol. 93 (2019), 673--686.
[9]
Gordon Fraser, Ute Heuer, Nina Körber, Florian Obermüller, and Ewald Wasmeier. 2021. LitterBox: A Linter for Scratch Programs. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET). 183--188. https://doi.org/10.1109/ICSE-SEET52601.2021.00028
[10]
Christoph Frädrich, Florian Obermüller, Nina Körber, Ute Heuer, and Gordon Fraser. 2020. Common Bugs in Scratch Programs. In Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education (Trondheim, Norway) (ITiCSE '20). 89--95. https://doi.org/10.1145/3341525.3387389
[11]
Google Developers. 2021. Blockly. https://developers.google.com/blockly/ Retrieved January 2, 2023 from
[12]
Isabella Graßl and Gordon Fraser. 2022a. Gender-dependent Contribution, Code and Creativity in a Virtual Programming Course. In Proceedings of the 17th Workshop in Primary and Secondary Computing Education. 1--10.
[13]
Isabella Graßl and Gordon Fraser. 2022b. Scratch as Social Network: Topic Modeling and Sentiment Analysis in Scratch Projects. arXiv preprint arXiv:2204.05902 (2022).
[14]
Luisa Greifenstein, Isabella Graßl, and Gordon Fraser. 2021. Challenging but Full of Opportunities: Teachers' Perspectives on Programming in Primary Schools. In 21st Koli Calling International Conference on Computing Education Research. 1--10.
[15]
Wolfgang Greller and Hendrik Drachsler. 2012. Translating learning into numbers: A generic framework for learning analytics. Journal of Educational Technology & Society, Vol. 15, 3 (2012), 42--57.
[16]
Elisabeth Griebl, Benedikt Fein, Florian Obermüller, Gordon Fraser, and René Just. 2023. On the Applicability of Language Models to Block-Based Programs. arXiv preprint arXiv:2302.03927 (2023).
[17]
VMware Inc. 2023. Spring Boot. https://spring.io/projects/spring-boot Retrieved January 2, 2023 from
[18]
Max Kesselbacher and Andreas Bollin. 2019. Discriminating Programming Strategies in Scratch: Making the Difference between Novice and Experienced Programmers. In Proceedings of the 14th Workshop in Primary and Secondary Computing Education (Glasgow, Scotland, Uk) (WiPSCE'19). Association for Computing Machinery, New York, NY, USA, Article 20, 10 pages. https://doi.org/10.1145/3361721.3361727
[19]
Red Gate Software Ltd. 2023. Flyway. https://flywaydb.org/ Retrieved January 2, 2023 from
[20]
John Maloney, Mitchel Resnick, Natalie Rusk, Brian Silverman, and Evelyn Eastmond. 2010. The Scratch Programming Language and Environment. ACM Transactions on Computing Education (TOCE), Vol. 10 (11 2010), 16. https://doi.org/10.1145/1868358.1868363
[21]
Monica M McGill and Adrienne Decker. 2020. Tools, languages, and environments used in primary and secondary computing education. In Proceedings of the 2020 ACM conference on innovation and technology in computer science education. 103--109.
[22]
MIT Media Lab. 2021. Scratch-Blocks. https://github.com/LLK/scratch-blocks Retrieved January 2, 2023 from
[23]
Jesús Moreno-León, Gregorio Robles, and Marcos Román-González. 2015. Dr. Scratch: Automatic analysis of scratch projects to assess and foster computational thinking. RED. Revista de Educación a Distancia 46 (2015), 1--23.
[24]
Florian Obermüller, Ute Heuer, and Gordon Fraser. 2021. Guiding next-step hint generation using automated tests. In Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 1. 220--226.
[25]
Go Ota, Yosuke Morimoto, and Hiroshi Kato. 2016. Ninja code village for scratch: Function samples/function analyser and automatic assessment of computational thinking concepts. In 2016 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). IEEE, 238--239.
[26]
Sue Sentance and Andrew Csizmadia. 2017. Computing in the curriculum: Challenges and strategies from a teacher's perspective. Education and Information Technologies, Vol. 22, 2 (2017), 469--495.
[27]
Milan J Srinivas, Michelle M Roy, Jyotsna N Sagri, and Viraj Kumar. 2018. Assessing scratch programmers' development of computational thinking with transaction-level data. In Towards extensible and adaptable methods in computing. Springer, 399--407.
[28]
Andreas Stahlbauer, Marvin Kreis, and Gordon Fraser. 2019. Testing scratch programs automatically. In Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering. 165--175.
[29]
Peeratham Techapalokul and Eli Tilevich. 2017a. Quality Hound - An online code smell analyzer for scratch programs. In 2017 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC). 337--338. https://doi.org/10.1109/VLHCC.2017.8103498
[30]
Peeratham Techapalokul and Eli Tilevich. 2017b. Understanding Recurring Quality Problems and Their Impact on Code Sharing in Block-Based Software. In 2017 IEEE Symposium on Visual Languages and Human -Centric Computing (VL /HCC ) (Raleigh, NC, USA, 2017--10). IEEE, 43--51. https://doi.org/10.1109/VLHCC.2017.8103449
[31]
Kimberly Williamson and Rene Kizilcec. 2022. A review of learning analytics dashboard research in higher education: implications for justice, equity, diversity, and inclusion. In LAK22: 12th International Learning Analytics and Knowledge Conference. 260--270.
[32]
Aman Yadav, Sarah Gretter, Susanne Hambrusch, and Phil Sands. 2016. Expanding computer science education in schools: understanding teacher experiences and challenges. Computer Science Education, Vol. 26, 4 (2016), 235--254.

Cited By

View all
  • (2024)NuzzleBug: Debugging Block-Based Programs in ScratchProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3623331(1-13)Online publication date: 20-May-2024
  • (2023)Impact of Hint Content on Performance and Learning: A Study with Primary School Children in a Scratch CourseProceedings of the 18th WiPSCE Conference on Primary and Secondary Computing Education Research10.1145/3605468.3605498(1-10)Online publication date: 27-Sep-2023

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cover image ACM Conferences
ITiCSE 2023: Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1
June 2023
694 pages
ISBN:9798400701382
DOI:10.1145/3587102
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 30 June 2023

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Author Tags

  1. block-based programming
  2. learning analytics
  3. scratch

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  • Research-article

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  • 01JA2021

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Cited By

View all
  • (2024)NuzzleBug: Debugging Block-Based Programs in ScratchProceedings of the IEEE/ACM 46th International Conference on Software Engineering10.1145/3597503.3623331(1-13)Online publication date: 20-May-2024
  • (2023)Impact of Hint Content on Performance and Learning: A Study with Primary School Children in a Scratch CourseProceedings of the 18th WiPSCE Conference on Primary and Secondary Computing Education Research10.1145/3605468.3605498(1-10)Online publication date: 27-Sep-2023

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