Giulia Paparo
ABSTRACT
With the “Lehrplan 21” school curriculum, a new subject “Media and Computer Science” was introduced in the German-speaking cantons of Switzerland. The curriculum defines competence areas that should be achieved by students within this subject. One such competence area is that middle school students should be able to develop executable and correct computer programs that use variables and subprograms. To evaluate and analyze how middle school students work with these more abstract CS concepts, we organized a Scratch Challenge – an online programming competition using the block-based programming language Scratch. We then compared the 203 submitted projects with an analysis of projects from the general Scratch repository. We found a similar use of types and quantities of blocks per projects (when considering projects developed in a short timeframe), but also an increased use of the targeted abstract concepts (especially of procedures), potentially influenced by the educational materials we provided for the challenge. Secondly, we examined the way middle school students work with these abstract concepts in Scratch, the errors they typically make, which challenges they face and the preconceptions they might have. These results contribute to the little studied area of middle school students working with more abstract concepts, such as variables, lists and procedures in Scratch. With this contribution, we hope to support schools to implement the aims of the “Lehrplan 21” successfully, and at the same time gain insight into the use of Scratch for teaching and learning more advanced CS concepts.
- Efthimia Aivaloglou and Felienne Hermans. 2016. How Kids Code and How We Know: An Exploratory Study on the Scratch Repository. In Proceedings of the 2016 ACM Conference on International Computing Education Research(Melbourne, VIC, Australia) (ICER ’16). ACM, New York, NY, USA, 53–61. https://doi.org/10.1145/2960310.2960325Google Scholar
Digital Library
- Bryce Boe, Charlotte Hill, Michelle Len, Greg Dreschler, Phillip Conrad, and Diana Franklin. 2013. Hairball: Lint-Inspired Static Analysis of Scratch Projects. In Proceeding of the 44th ACM Technical Symposium on Computer Science Education (Denver, Colorado, USA) (SIGCSE ’13). ACM, New York, NY, USA, 215–220. https://doi.org/10.1145/2445196.2445265Google ScholarDigital Library
- Karen Brennan, Christan Balch, and Michelle Chung. 2014. Creative Computing Curriculum Guide. ScratchEd. Retrieved July 20th, 2021 from https://scratched.gse.harvard.edu/resources/scratch-curriculum-guide.htmlGoogle Scholar
- Jacob Cohen. 1960. A Coefficient of Agreement for Nominal Scales. Educational and Psicological Measurement 20, 1 (Apr. 1960), 37–46. https://doi.org/10.1177/001316446002000104Google ScholarCross Ref
- Deutschschweizer Erziehungsdirektoren-Konferenz (D-EDK). 2016. Lehrplan 21 - von der D-EDK Plenarversammlung am 31.10.2014 zur Einführung in den Kantonen freigegebene Vorlage. Bereinigte Fassung vom 29.02.2016. D-EDK. Retrieved July 5th, 2021 from https://v-fe.lehrplan.ch/container/V_FE_DE_Modul_MI.pdfGoogle Scholar
- Beat Döbeli Honegger and Michael Hielscher. 2017. Vom Lehrplan zur LehrerInnenbildung - Erste Erfahrungen mit obligatorischer Informatikdidaktik für angehende Schweizer PrimarlehrerInnen. In Informatische Bildung zum Verstehen und Gestalten der digitalen Welt (Oldenburg, Germany) (INFOS 2017). Gesellschaft für Informatik, Bonn, Germany, 97–107.Google Scholar
- Deborah A. Fields, Michael Giang, and Yasmin Kafai. 2014. Programming in the Wild: Trends in Youth Computational Participation in the Online Scratch Community. In Proceedings of the 9th Workshop in Primary and Secondary Computing Education (Berlin, Germany) (WiPSCE ’14). ACM, New York, NY, USA, 2–11. https://doi.org/10.1145/2670757.2670768Google ScholarDigital Library
- Alexandra Funke and Katharina Geldreich. 2017. Gender Differences in Scratch Programs of Primary School Children. In Proceedings of the 12th Workshop on Primary and Secondary Computing Education(Nijmegen, Netherlands) (WiPSCE ’17). ACM, Nijmegen Netherlands, 57–64. https://doi.org/10.1145/3137065.3137067Google ScholarDigital Library
- Alexandra Funke, Katharina Geldreich, and Peter Hubwieser. 2017. Analysis of Scratch Projects of an Introductory Programming Course for Primary School Students. In 2017 IEEE Global Engineering Education Conference(Athens, Greece) (EDUCON). IEEE, New York, NY, USA, 1229–1236. https://doi.org/10.1109/EDUCON.2017.7943005Google ScholarCross Ref
- Shuchi Grover, Roy Pea, and Stephen Cooper. 2015. Designing for deeper learning in a blended computer science course for middle school students. Computer Science Education 25, 2 (2015), 199–237. https://doi.org/10.1080/08993408.2015.1033142 arXiv:https://doi.org/10.1080/08993408.2015.1033142Google ScholarCross Ref
- Brian Harvey and Jens Mönig. 2010. Bringing “No Ceiling” to Scratch: Can One Language Serve Kids and Computer Scientists?Constructionism 2010 (Jan. 2010), 1–10.Google Scholar
- J. Richard Landis and Gary G. Koch. 1977. The Measurement of Observer Agreement for Categorical Data. Biometrics 33, 1 (Mar. 1977), 159–174. https://doi.org/10.2307/2529310Google ScholarCross Ref
- Kevin Lawanto, Kevin Close, Clarence Ames, and Sarah Brasiel. 2017. Exploring Strengths and Weaknesses in Middle School Students’ Computational Thinking in Scratch. In Emerging Research, Practice, and Policy on Computational Thinking, Peter J. Rich and Charles B. Hodges (Eds.). Springer International Publishing, Cham, 307–326. https://doi.org/10.1007/978-3-319-52691-1_19Google Scholar
- John H. Maloney, Kylie Peppler, Yasmin Kafai, Mitchel Resnick, and Natalie Rusk. 2008. Programming by Choice: Urban Youth Learning Programming with Scratch. In Proceedings of the 39th SIGCSE Technical Symposium on Computer Science Education (Portland, OR, USA) (SIGCSE ’08). ACM, New York, NY, USA, 367–371. https://doi.org/10.1145/1352135.1352260Google ScholarDigital Library
- Philipp Mayring. 2000. Qualitative Content Analysis. Forum Qualitative Sozialforschung / Forum: Qualitative Social Research 1, 2 (Jun. 2000), 2–10. https://doi.org/10.17169/fqs-1.2.1089Google Scholar
- Orni Meerbaum-Salant, Michal Armoni, and Mordechai (Moti) Ben-Ari. 2013. Learning computer science concepts with Scratch. Computer Science Education 23, 3 (2013), 239–264. https://doi.org/10.1080/08993408.2013.832022 arXiv:https://doi.org/10.1080/08993408.2013.832022Google ScholarCross Ref
- 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 (Sep. 2015), 23.Google Scholar
- Jesús Moreno-León, Gregorio Robles, and Marcos Román-González. 2020. Towards Data-Driven Learning Paths to Develop Computational Thinking with Scratch. IEEE Transactions on Emerging Topics in Computing 8, 1 (2020), 193–205. https://doi.org/10.1109/TETC.2017.2734818Google ScholarCross Ref
- Sofia Papavlasopoulou, Michail Giannakos, and Letizia Jaccheri. 2018. Discovering Children’s Competences in Coding Through the Analysis of Scratch Projects. In 2018 IEEE Global Engineering Education Conference(Santa Cruz de Tenerife, Spain) (EDUCON). IEEE, New York, NY, USA, 1127–1133. https://doi.org/10.1109/EDUCON.2018.8363356Google Scholar
- Mitchel Resnick, John Maloney, Andrés Monroy-Hernández, Natalie Rusk, Evelyn Eastmond, Karen Brennan, Amon Millner, Eric Rosenbaum, Jay Silver, Brian Silverman, and Yasmin Kafai. 2009. Scratch: Programming for All. Commun. ACM 52, 11 (Nov. 2009), 60–67. https://doi.org/10.1145/1592761.1592779Google ScholarDigital Library
- Alaaeddin Swidan, Alexander Serebrenik, and Felienne Hermans. 2017. How do Scratch Programmers Name Variables and Procedures?. In 2017 IEEE 17th International Working Conference on Source Code Analysis and Manipulation (Shanghai, China) (SCAM). IEEE, New York, NY, USA, 51–60. https://doi.org/10.1109/SCAM.2017.12Google ScholarCross Ref
- Xiaodan Tang, Yue Yin, Qiao Lin, Roxana Hadad, and Xiaoming Zhai. 2020. Assessing Computational Thinking: A Systematic Review of Empirical Studies. Computers & Education 148 (Apr. 2020), 1–22. https://doi.org/10.1016/j.compedu.2019.103798Google ScholarDigital Library
- Giovanni Maria Troiano, Sam Snodgrass, Erinç Argımak, Gregorio Robles, Gillian Smith, Michael Cassidy, Eli Tucker-Raymond, Gillian Puttick, and Casper Harteveld. 2019. Is My Game OK Dr. Scratch? Exploring Programming and Computational Thinking Development via Metrics in Student-Designed Serious Games for STEM. In Proceedings of the 18th ACM International Conference on Interaction Design and Children (Boise, ID, USA) (IDC ’19). ACM, New York, NY, USA, 208–219. https://doi.org/10.1145/3311927.3323152Google ScholarDigital Library
- Heidi Webb and Mary Beth Rosson. 2013. Using Scaffolded Examples to Teach Computational Thinking Concepts. In Proceeding of the 44th ACM technical symposium on Computer science education (Denver, Colorado, USA) (SIGCSE ’13). ACM, New York, NY, USA, 95–100. https://doi.org/10.1145/2445196.2445227Google ScholarDigital Library
- Xuefeng Wei, Lin Lin, Nanxi Meng, Wei Tan, Siu-Cheung Kong, and Kinshuk. 2021. The Effectiveness of Partial Pair Programming on Elementary School Students’ Computational Thinking Skills and Self-Efficacy. Computers & Education 160 (Jan. 2021), 1–49. https://doi.org/10.1016/j.compedu.2020.104023Google Scholar
- Scratch Wiki. 2021. List. Scratch. Retrieved July 15th, 2021 from https://en.scratch-wiki.info/wiki/ListGoogle Scholar
- Ad Zeevaarders and Efthimia Aivaloglou. 2021. Exploring the Programming Concepts Practiced by Scratch Users: an Analysis of Project Repositories. In 2021 IEEE Global Engineering Education Conference (Vienna, Austria) (EDUCON). IEEE, New York, NY, USA, 1287–1295. https://doi.org/10.1109/EDUCON46332.2021.9453973Google ScholarCross Ref
Recommendations
Factors Influencing Lower Secondary School Pupils’ Success in Programming Projects in Scratch
Informatics in Schools. Engaging Learners in Computational ThinkingAbstractIn the Czech Republic, a radical change in the school curriculum is planned. Through a new, compulsory subject of “Informatics and ICT”, the aim is to develop digital literacy across all school subjects, and computational thinking. Computational ...
Exploring Math + CS in a Secondary Education Methods Course
SIGCSE 2022: Proceedings of the 53rd ACM Technical Symposium on Computer Science Education - Volume 1There is wide-spread agreement that K-12 students need opportunities to explore computer science (CS) concepts and computational thinking within a wide array of disciplines for advancing, broadening, and diversifying the participation in CS. Programs ...
Spreading the word: introducing pre-service teachers to programming in the K12 classroom
SIGCSE '14: Proceedings of the 45th ACM technical symposium on Computer science educationWe present our experiences and outcomes from a programming camp held for sixth through ninth grade students. The instructional team included five pre-service teachers who earned field experience credit for this work, and one in-service teacher. The pre-...
Comments