How to Improve Computational Thinkinga Case Study

  1. Quitério Figueiredo, José Alberto 1
  1. 1 Unidade de Investigação para o Desenvolvimento do Interior, Instituto Politécnico da Guarda, Portugal
Journal:
Education in the knowledge society (EKS)

ISSN: 2444-8729,  1138-9737

Year of publication: 2017

Volume: 18

Issue: 4

Pages: 35-51

Type: Article

DOI: 10.14201/EKS20171843551 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Education in the knowledge society (EKS)

Abstract

One of the best skills for everyone, for now, and for the future, is problem-solving. Computational thinking is the way to help us to develop that skill. Computational Thinking can be defined as a set of skills for problemsolving based on computer techniques. Computational thinking is needed everywhere and is going to be a key to success in almost all careers, not only for a scientist but for many professionals, like doctors, lawyers, teachers or farmers. For many problems it is a good idea to make a plan for its resolution using some of the techniques of computer science, such as: breaking down a complex problem into smaller parts that are more manageable and easier to understand, or solve—decomposition; looking for similarities among and within problems and others experiences—pattern recognition; focusing on the important information only, and pulling out specific differences to make one solution work for multiple problems: abstraction; developing a step-by-step solution to the problem: algorithms. This plan can be used by everyone, regardless of their area of knowledge, task or age. It is essential that these techniques are practiced and developed very early. In recent years we have to see the proliferation of numerous projects with the specific objective of encouraging the study of Computational thinking. The projects of massification of computational thinking and coding are now starting to be implemented in our education system in Portugal. Most students of the first year of the Computer Engineering course, from the IPG, mostly did not have the opportunity to develop computational thinking throughout their student life. In this paper, we present the results of a case study using follow and give instructions to improve their capacities in Computational Thinking..

Bibliographic References

  • Alice – Tell Stories. Build Games. Learn to Program. (n.d.). Retrieved July 5, 2017, from http://www.alice.org/
  • App Inventor for Educators – MIT App Inventor Educators Community. (n.d.). Retrieved July 6, 2017, from http://teach.appinventor.mit.edu/
  • Blockly | Google Developers. (n.d.). Retrieved July 6, 2017, from https://developers.google.com/blockly/
  • CodeCombat - Learn how to code by playing a game. (n.d.). Retrieved July 5, 2017, from https://codecombat.com/
  • Coding for Kids | Tynker. (n.d.). Retrieved July 5, 2017, from https://www.tynker.com/Computer Science Education Week. (n.d.). Retrieved July 5, 2017, from https://csedweek.org/
  • Computer Science Unplugged. (n.d.). Retrieved July 5, 2017, from http://csunplugged.org/Computing At School. (n.d.). Retrieved July 6, 2017, from http://www.computingatschool.org.uk/
  • Cooper, S., Wang, K., Israni, M. & Sorby, S. (2015). Spatial Skills Training in Introductory Computing. Proceedings of the Eleventh Annual International Conference on International Computing Education Research, 13-20. http://doi.org/10.1145/2787622.2787728
  • Cubetto: A robot teaching kids code & computer programming. (n.d.). Retrieved August 6, 2017, from https://www.primotoys.com/
  • Denny, P., Luxton-Reilly, A. & Simon, B. (2008). Evaluating a new exam question: Parsons problems. Proceedings of the Fourth International Workshop on Computing Education Research, 113-124. http://doi.org/10.1145/1404520.1404532
  • Ericson, B. J. (2014). Adaptive Parsons Problems with Discourse Rules. Icer ’14, 145-146. http://doi.org/10.1145/2632320.2632324
  • Falomir, Z. (2016). Towards A Qualitative Descriptor for Paper Folding Reasonin. In Proc. of the 29th International Workshop on Qualitative Reasoning (QR’16). New York, USA.
  • Figueiredo, J., Gomes, N. & García-Peñalvo, F. J. (2016). Ne-course for learning programming. In Proceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality - TEEM ’16 (pp. 549–553). New York, New York, USA: ACM Press. http://doi.org/10.1145/3012430.3012572
  • Fincher, S., Baker, B., Box, I., Cutts, Q., Raadt, M. De, Haden, P., … Tutty, J. (2005). Computer Science at Kent programming courses, (1).
  • García-Peñalvo, F. J. (2016a). A brief introduction to TACCLE 3 – Coding European Project. In F. J. García-Peñalvo & J. A. Mendes (Eds.), 2016 International Symposium on Computers in Education (SIIE16). USA: IEEE. http://doi.org/10.1109/SIIE.2016.7751876
  • García-Peñalvo, F. J. (2016b). Proyecto TACCLE3 – Coding. In F. J. García-Peñalvo & J. A. Mendes (Eds.), XVIII Simposio Internacional de Informática Educativa, SIIE 2016 (pp. 187-189). Salamanca, España: Ediciones Universidad de Salamanca.
  • García-Peñalvo, F. J. (2016c). What Computational Thinking Is. Journal of Information Technology Research, 9(3), v-viii.
  • García-Peñalvo, F. J. & Cruz-Benito, J. (2016). Computational thinking in pre-university education. In Proceedings of the Fourth International Conference on Technological Ecosystems for Enhancing Multiculturality - TEEM ’16 (pp. 13-17). New York, New York, USA: ACM Press. http://doi.org/10.1145/3012430.3012490
  • García-Peñalvo, F. J., Hughes, J., Rees, A., Jormanainen, I., Toivonen, T., Reimann, D., . . . Virnes, M. (2016). Evaluation of existing resources (study/analysis). Belgium: TACCLE3 Consortium. http://doi.org/10.5281/zenodo.163112
  • García-Peñalvo, F. J., Llorens Largo, F., Molero Prieto, X. & Vendrell Vidal, E. (2017). Educación en Informática sub 18 (EI<18). ReVisión, 10(2), 13-18.
  • García-Peñalvo, F. J., Reimann, D., Tuul, M., Rees, A. & Jormanainen, I. (2016). An overview of the most relevant literature on coding and computational thinking with emphasis on the relevant issues for teachers. Belgium: TACCLE3 Consortium. http://doi.org/10.5281/zenodo.165123.
  • Greenfoot | About Greenfoot. (n.d.). Retrieved July 7, 2017, from https://www.greenfoot.org/overview
  • Home - Barefoot Computing Barefoot Computing. (n.d.). Retrieved July 5, 2017, from https://barefootcas.org.uk/
  • Israel, M., Wherfel, Q. M., Pearson, J., Shehab, S. & Tapia, T. (2015). Empowering K-12 Students with Disabilities to Learn Computational Thinking and Computer Programming. TEACHING Exceptional Children, 48(1), 45-53. http://doi.org/10.1177/0040059915594790
  • Jaeger, A. J., Wiley, J., Pellegrino, J., Zinsser, K., Stieff, M. & Moher, T. (2015). What Does the Punched Holes Task Measure?
  • Khan Academy | Free Online Courses, Lessons &amp; Practice. (n.d.). Retrieved July 5, 2017, from https://www.khanacademy.org/
  • Lightbot. (n.d.). Retrieved July 5, 2017, from https://lightbot.com/flash.html
  • LiveCode Ltd. (n.d.). LiveCode in Education | LiveCode. Retrieved July 6, 2017, from https://livecode.com/products/livecode-platform/livecode-in-education/
  • Llorens Largo, F., García-Peñalvo, F. J., Molero Prieto, X. & Vendrell Vidal, E. (2017). La enseñanza de la informática, la programación y el pensamiento computacional en los estudios preuniversitarios. Education in the Knowledge Society, 18(2), 7-17. http://doi.org/10.14201/eks2017182717
  • Microsoft Touch Develop - create apps everywhere, on all your devices! (n.d.). Retrieved July 6, 2017, from https://www.touchdevelop.com/
  • MIT App Inventor. (n.d.). Retrieved July 5, 2017, from http://ai2.appinventor.mit.edu/
  • Morrison, B. B., Margulieux, L. E., Ericson, B. & Guzdial, M. (2016). Subgoals Help Students Solve Parsons Problems. Proceedings of the 47th ACM Technical Symposium on Computing Science Education, 42-47. http://doi.org/10.1145/2839509.2844617
  • Mselle, L. J. & Twaakyondo, H. (2012). The impact of Memory Transfer Language (MTL) on reducing misconceptions in teaching programming to novices. International Journal of Machine Learning and Applications, 1(1), 1-6. http://doi.org/10.4102/ijmla.v1i1.3
  • National Research Council. (2012). A Framework for K-12 Science Education. Practices, Crosscutting Concepts, and Core Ideas. Washington, D.C.: National Academies Press. http://doi.org/10.17226/13165
  • Nestojko, J. F., Bui, D. C., Kornell, N. & Bjork, E. L. (2014). Expecting to teach enhances learning and organization of knowledge in free recall of text passages. Memory & Cognition, 42(7), 1038-1048. http://doi.org/10.3758/s13421-014-0416-z
  • Pinto-Llorente, A. M., Casillas-Martín, S., Cabezas-González, M. & García-Peñalvo, F. J. (2017). Building, coding and programming 3D models via a visual programming environment. Quality & Quantity, In Press. http://doi.org/10.1007/s11135-017-0509-4
  • Programming for Kids | Kodable. (n.d.). Retrieved July 5, 2017, from https://www.kodable.com/
  • Scratch - Imagine, Program, Share. (n.d.). Retrieved July 5, 2017, from https://scratch.mit.edu/
  • Simon, Fincher, S., Robins, A., Baker, B., Box, I., Cutts, Q., … Tutty, J. (2006). Predictors of success in a first programming course. Proceedings of the 8th Austalian Conference on Computing Education - Volume 52, 189-196. http://doi.org/10.1145/953051.801357
  • Snap! (Build Your Own Blocks) 4.0. (n.d.). Retrieved July 10, 2017, from http://snap.berkeley.edu/index.html
  • STEM. (n.d.). Retrieved July 6, 2017, from https://www.stem.org.uk/
  • Study, N. E. (2012). An Overview of Tests of Cognitive Spatial Ability. 66th EDGD Mid-Year Conference Proceedings. Retrieved from https://goo.gl/YwnYrv
  • Taccle 3 – Supporting primary teachers to teach coding. (n.d.). Retrieved July 5, 2017, from http://www.taccle3.eu/en/
  • techliteracy. (n.d.). Retrieved July 6, 2017, from https://techliteracy.co.uk/
  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33-35. http://doi.org/10.1145/1118178.1118215
Data source: Dialnet