Creativity in Solving Short Tasks for Learning Computational Thinking
Valentina Dagienė, Gerald Futschek & Gabrielė Stupurienė
Log in to download the full text for free
> Citation
> Similar
> References
> Add Comment
Abstract
Context: The increasing and evolving presence of technology in the lives of children is reflected in the recognition in many educational frameworks that students should possess and be able to demonstrate computational thinking skills as part of their problem-solving practice. Problem: We discuss the process of creating tasks for the so-called Bebras challenge, a contest on informatics (computing) and computational thinking addressing school students of all ages. These tasks have a short problem statement and should be solvable in a few minutes. The challenge explored is how to formulate and structure such tasks so that there is still enough space for creativity in the solution process and how to organize the learning settings so that constructionist learning is supported. Method: We give an experience report about the creation and use of short tasks for learning computational thinking. We argue that the constructionist perspective involving the use of the Bebras-like tasks on computational thinking offers an appropriate frame for enriching learning activities, fostering collaborative and individual creativity. A process-oriented approach was selected for the research done in a study where we observed children’s activities in solving the short tasks on computational thinking. Results: Our analysis of the creativity, as exemplified in several observations of pupils while solving short tasks that involve computing concepts (the Bebras cards), shows that this kind of microlearning serves well to motivate pupils to be more interested in particular computing topics. The concept of the short tasks meets the usual way of teaching in primary education. Pupils and teachers develop a positive attitude to computing related topics. The analysis shows that the short tasks encourage pupils’ creativity in both solving and modifying them. Implications: Our study provides some preliminary evidence that, from a constructionist perspective, collective as well as individual creativity can stand as an appropriate framework for designing learning activities addressing computing concepts and supporting computational thinking. Moreover, our study opens a new field of research in combining creativity and computational thinking from a constructionist perspective. Constructivist content: Our more general aim is to support computing education, especially constructivist learning environments (both technology-based environments and those without technologies) in primary education.
Key words: Constructionism, creativity, computing (informatics) education, computing-concepts-based task, microlearning, short task, Bebras-like tasks, primary education
Citation
Dagienė V., Futschek G. & Stupurienė G. (2019) Creativity in solving short tasks for learning computational thinking. Constructivist Foundations 14(3): 382–396. https://constructivist.info/14/3/382
Export article citation data:
Plain Text ·
BibTex ·
EndNote ·
Reference Manager (RIS)
Similar articles
References
Behringer R. (2013) Interoperability standards for MicroLearning. In: Proceedings of the MicroLearning conference. Stift Göttweig, Austria, 26–27 September 2013.
▸︎ Google︎ Scholar
Bischof E., Sabitzer B. (2011) Computer science in primary schools – Not possible, but necessary?! In: Kalaš I. & Mittermeir R. T. (eds.) Informatics in schools: Contributing to 21st century education. Proceedings of the ISSEP 2011 conference. Springer, Berlin: 94–105.
▸︎ Google︎ Scholar
Blair C. (2006) How similar are fluid cognition and general intelligence? A developmental neuroscience perspective on fluid cognition as an aspect of human cognitive ability. Behavioral and Brain Sciences 29(2): 109–125.
▸︎ Google︎ Scholar
Bourn D. (2018) From 21st century skills to global skills. Chapter 4 in: Understanding global skills for 21st century professions. Palgrave Macmillan, Cham: 63–85.
▸︎ Google︎ Scholar
Bull P. H. & Patterson G. C. (2016) Strategies to promote pedagogical knowledge interplay with technology. In: Keengwe J. & Onchwari G. (eds.) Handbook of research on active learning and the flipped classroom model in the digital age. IGI Global, Hershey PA: 255–271.
▸︎ Google︎ Scholar
Cobern W. W. (1993) Contextual constructivism: The impact of culture on the learning and teaching of science. In: Tobin K. (ed.) The practice of constructivism in science education. Lawrence Erlbaum Associates, Hillsdale NJ: 51–69
https://cepa.info/3053
Corradini I., Lodi M. & Nardelli E. (2017) Conceptions and misconceptions about computational thinking among Italian primary school teachers. In: Proceedings of the 2017 ACM conference on international computing education research. ACM, New York: 136–144.
▸︎ Google︎ Scholar
Craft A. (2008) Studying collaborative creativity: Implications for education. Thinking Skills and Creativity 3(3): 241–245.
▸︎ Google︎ Scholar
Cropley A. J. (2001) Creativity in education & learning: A guide for teachers and educators. Psychology Press, Hove UK.
▸︎ Google︎ Scholar
Davis R. B. (2013) Conceptual and procedural knowledge in mathematics: A summary analysis. In: Hiebert J. (ed.) Conceptual and procedural knowledge: The case of mathematics. Routledge, London: 281–316.
▸︎ Google︎ Scholar
Duncan C. & Bell T. (2015) A pilot computer science and programming course for primary school students. In: Proceedings of the workshop in primary and secondary computing education. ACM, New York: 39–48.
▸︎ Google︎ Scholar
Grover S. & Pea R. (2013) Computational thinking in K-12: A review of the state of the field. Educational Researcher 42(1): 38–43.
▸︎ Google︎ Scholar
Hammond J. & Gibbons P. (2005) What is scaffolding? In: Burns A. & de Silva Joyce H. (eds.) Teachers’ Voices 8: Explicitly supporting reading and writing in the classroom. Macquarie University, Sydney: 8–16.
▸︎ Google︎ Scholar
Heintz F., Mannila L. & Färnqvist T. (2016) A review of models for introducing computational thinking, computer science and computing in K-12 education. In: 2016 IEEE Frontiers in Education conference (FIE). IEEE Press, Piscataway NJ: 1–9.
▸︎ Google︎ Scholar
Juškevičienė A. & Dagienė V. (2018) Computational thinking relationship with digital competence. Informatics in Education 17(2): 265–284.
▸︎ Google︎ Scholar
Kafai Y. B. (2006) Constructionism. In: Sawyer R. K. (ed.) Cambridge handbook of the learning sciences. Cambridge University Press, Cambridge MA: 34–46.
▸︎ Google︎ Scholar
Kalelioğlu F., Gülbahar Y. & Kukul V. (2016) A framework for computational thinking based on a systematic research review. Baltic Journal of Modern Computing 4(3): 583–596.
▸︎ Google︎ Scholar
Kaufman J. C. & Beghetto R. A. (2009) Beyond big and little: The four C model of creativity. Review of General Psychology 13(1): 1–12.
▸︎ Google︎ Scholar
Lave J. (2008) Everyday life and learning. In: Murphy P. & McCormick R. (eds.) Knowledge and practice: Representations and Identities. SAGE, London: 3–14.
▸︎ Google︎ Scholar
Lee I., Martin F., Denner J., Coulter B., Allan W., Erickson J., Malyn-Smith J. & Werner L. (2011) Computational thinking for youth in practice. ACM Inroads 2(1): 32–37.
▸︎ Google︎ Scholar
Mannila L., Nordén L. Å. & Pears A. (2018) Digital competence, teacher self-efficacy and training needs. In: Proceedings of the 2018 ACM conference on international computing education research. ACM, New York: 78–85.
▸︎ Google︎ Scholar
McCormick R. (1997) Conceptual and procedural knowledge. International Journal of Technology and Design Education 7(1–2): 141–159.
▸︎ Google︎ Scholar
Mohammed G. S., Wakil K. & Nawroly S. S. (2018) The effectiveness of microlearning to improve students’ learning ability. International Journal of Educational Research Review 3(3): 32–38.
▸︎ Google︎ Scholar
Pohl W. & Hein H. W. (2015) Aspects of quality in the presentation of informatics challenge tasks. In: Diethelm I. & Mittermeir R. T. (eds.) Proceedings of the international conference on informatics in schools: Situation, evolution and perspectives. Springer, Heidelberg: 21–32.
▸︎ Google︎ Scholar
Star J. R. & Stylianides G. J. (2013) Procedural and conceptual knowledge: Exploring the gap between knowledge type and knowledge quality. Canadian Journal of Science, Mathematics and Technology Education 13(2): 169–181.
▸︎ Google︎ Scholar
Webb M. E., Bell T., Davis N., Katz Y. J., Fluck A., Sysło M. M., Kalaš I., Cox M., Angeli C., Malyn-Smith J. & Brinda T. (2018) Tensions in specifying computing curricula for K-12: Towards a principled approach for objectives. it – Information Technology 60(2): 59–68.
▸︎ Google︎ Scholar
Webb M., Davis N., Bell T., Katz Y. J., Reynolds N., Chambers D. P. & Sysło M. M. (2017) Computer science in K-12 school curricula of the 21st century: Why, what and when? Education and Information Technologies 22(2): 445–468.
▸︎ Google︎ Scholar
Weigend M., Pluhár Z., Juškevičienė A., Vaníček J., Ito K., Pesek I. (2018) Constructionism in the classroom: Creative learning activities on computational thinking. In: Valentina D. & Jasutė E. (eds.) Constructionism, computational thinking and educational innovation: Conference proceedings. Vilnius University, Vilnius: 891–907.
▸︎ Google︎ Scholar
Weintrop D., Beheshti E., Horn M., Orton K., Jona K., Trouille L. & Wilensky U. (2016) Defining computational thinking for mathematics and science classrooms. Journal of Science Education and Technology 25(1): 127–147.
▸︎ Google︎ Scholar
Comments: 0
To stay informed about comments to this publication and post comments yourself, please log in first.
