How is the best method to teach computational thinking to children?
Nowadays our society is convinced that the world is moving quickly forward to the digital format. As a result, specific new skills are needed, such as computer programming. On the one side it is called Language of the Numbers, on the other side coding is basically to create a sequence of instructions that a computer reads and executes to automatically generate an image, a web page or an application for smartphones for example (Gardiner, 2014). In the same article, Gardiner listed a huge number of countries that include coding in the official curriculum, like Estonia, England, Singapore, The United States and others (Gardiner, 2014). Furthermore, as early as possible, teaching to code is better absorbed (Gardiner, 2014). Moreover, within a strongly defined position, Pérez-Marín and others (2020), show the computational thinking as a key skill in the 21st century and defined the skill involved it with a list of abilities such as solving problems, designing systems, and understanding human behavior based on computer science concepts (Pérez-Marín et al., 2020). In this context, the foundation question is how to do it in the best way? But still not clear how a procedure can be developed in children, with different pedagogical methodologies being researched to be used to do it (Pérez-Marín et al., 2020). In this essay the discussion will involve three ways that computational thinking can be acquired such as Unplugged Activities (Brackmann et al., 2016), Educational Robotics (Bers et al., 2010), and Programming Computers (Pérez-Marín et al., 2020). This exchange of views is moving to the conclusion that preparing educationists to teach to code computers is the finest solution.
First of all, not so long ago, the computers did not have much space to storage, the memories were a very slow process and each task, even for doing the simplest actions, the line wrote code was necessary (Crow, 2014). Nowadays the people have mini-computers with more than 100,000 times faster processors than an older ZX81 PC, for example (Crow, 2014). Furthermore, with instantaneous access, a huge amount of human data knowledge can be accessed on the world wide web, and the computing changed pace was extraordinary, as quoted by (Crow, 2014). Moreover, considering Mr. Turing as one of the geniuses of computing of the 20th century, Britain had a proud history and modern computer ideas were based on theoretical and practical work from him (Crow, 2014). Historically detailed, started the 1980s with their boom of home-computers sales and the launched of internet, created by Mr. Sir Tim Berners-Lee, throughout the 1990s when the education about programming computers was largely ignored instead a simple word document write was teaching, to today (2014), when a new British curriculum includes code computing, that year was named “the year of the code” (Crow, 2014). In addition, acquainted with the range between simple coding and advanced computer programming, students in all grades have been in contact with this technology (Gardiner, 2014). Without forgetting the possibility of future careers, this knowledge is also important for their countries, on this account where the industries need workers more qualified and the economy is increasing in digital transformation. It can also be argued that comprehensive ideas from programming, when introduced at an early age, changed the perspective of children relationed to this field (Gardiner, 2014). In addition, the same enhanced skills to computers, are being able to develop problem-solving abilities at a younger age. (Gardiner, 2014).
Secondly, considered by the author a good approach to teaching Computer Science to children, is to attend unplugged activities, sometimes using open documents or exercises like as disponible from website Code.org, or using storytelling to create evolving in young children (Pérez-Marín et al., 2020). In supplementation, these techniques were used especially in developing countries, when having a shortage of trained teachers (Brackmann et al., 2016).
In general, Brackmann exposed four techniques to accomplish the computational thinking problem solving, such as the first Decomposition Pilar, where the child divided complex problem into small-scale, as a result, made easier to be in control of it, the second is called Pattern Recognition pillar, where considering pre-solved problems, the parts divided can be analyzed deependly to forming general conceptions and discussed one a one, the third is Abstraction Pillar, when the irrelevant information was withdrawal from the game moving the focus to the important details, and the fourth is Algorithm Pillar, where students could create phases or conditionals steps in front of divided-problems to solve them (Brackmann et al., 2016). In addition, in the same article when the analysis was enhanced, the author exposed the difficulties and differences that the research found in some countries. The problems such as teachers without preparation, rarely structure of hardware and software, and difficulties to access the internet appear in France, United States, and others (Brackmann et al., 2016). In contrast, countries like Australia and New Zealand with one computer per student, or Sweden and Portugal that have one computer to share only for two students, show increased development in educating (Brackmann et al., 2016). Furthermore, the authors suggest in their conclusion, applying a disconnected procedure, also called unplugged way or Unplugged Activities, consider each of the pillars cited below, could be a better solution to almost all countries listed (Brackmann et al., 2016).
Moreover, another addressed way is Robotics. Cogitate about the early introduction, between four and seven years age child, engineering and programming a physical object produces a powerful learning to them (Bers et al., 2006). The most popular and accessible gadget that put forward a theoretical introduction to robotic technology and is practically used is named LEGO® bricks. Also explained about, Bers et al.(2016) quote that parents and children need interactions together, when problem-solving skills could also be developed, and these involve helping other interactions with teachers and tutors of robotics. (Bers et al., 2006) Moving forward, Bers made another discussion, pass-through more than ten years in research, developing a system assessed the human-made world, immersed in the dominion of technology and engineering, named Tangiblek, that is a robotic program used to teach young children using natural words, numbers and letters (Bers, 2010). As a result, the youngs used these programs to profound computational thinking whereas they just created and applied design process and minimal engineering was needed (Bers, 2010). Although every level of education had a specific group of knowledge, the research applied gave relevant results when showing a connection between developing youth in TangibleK and the table of contents in official curriculum grade (Bers, 2010). Moving to the end of both articles, applying developmentally appropriate methods, the robotics learning uses can actively engage young children to develop Computational thinking (Bers et al., 2006) and (Bers, 2010).
At last, but not least, make a proposal to teach programming computers to young people on objective in developing computational thinking needs to be deepened and debated. Conducting a structured experiment escorted by unambiguous measures could be an option. Following this orientation, (Pérez-Marín et al., 2020) present in their article a test with 132 primary education students (9–12 years in age) at the beginning of the experiment, and another test at the end, with analysis to measure their CT (computational thinking). These tests gave support a thesis that some authors claimed that CT can be acquired and developed by teaching programming to children (Pérez-Marín et al., 2020). Moreover, since childhood, almost all young people are naturally fascinated by technology. Children love computers and do not think that they are boring to use, in fact, these feelings gave more attention during the lessons notwithstanding their grade (Pérez-Marín et al., 2020). Giving thought in results analysis, learning how to program is engaging, helps to focus on problems and grow as positive experiences with children age 9 to 12. Still in results “there is a statistically significant increase in children’s post-test results both in knowledge and Computational Thinking values for all grades”. (Pérez-Marín et al., 2020). To sum up, teaching programming computers is the best solution to get good computational thinking.
To summarize, the approach to problem solving, based on a computer vision thinking, could helps anyone to manage and tackle sizeable problems into a sequence of little, considering an acceptable level of abstraction, creating real word based models focused on appropriate aspects, helps to find a enhanced solution (Crow, 2014). Furthermore, in the same article, Crow explained about how this approach reaches out beyond writing software, including as long as areas such as engineering mechanical, fluids mechanics, physics, biology and others, still citing the business and markets with a potential use of computational analyses (Crow, 2014). In addition to that, Gardiner remembered a project named Code.org, that included computer science into every American School, that was working with more than 35,000 of teachers, training them to use tutorials from projects to classrooms (Gardiner, 2014). To finalize, Crow wrote “Anyone can learn to code. In a few hours you can pick up the basic skills and in a few weeks you will be able to build useful applications and websites” (Crow, 2014), and considering all sides and articles discussed and cited before, firstly the teachers need to receive tutoring and after, the children could be better introduced to this new Code-World based, understanding all benefits that learn programming computers will give to them.
References
Bers, M., Rogers, C., Beals, L., Portsmore, M., Staszowski, K., Cejka, E., Carberry, A., Gravel, B., Anderson, J., & Barnett, M. (2006). Innovative session: Early childhood robotics for learning. Proceedings of the 7th international conference on Learning sciences, 1036–1042.
Bers, M. U. (2010). The TangibleK Robotics Program: Applied Computational Thinking for Young Children. Early Childhood Research & Practice, 12(2). https://eric.ed.gov/?id=EJ910910
Brackmann, C., Barone, D., Casali, A., Boucinha, R., & Muñoz-Hernandez, S. (2016). Computational thinking: Panorama of the Americas. 2016 International Symposium on Computers in Education (SIIE), 1–6. https://doi.org/10.1109/SIIE.2016.7751839
Crow, D. (2014, fevereiro 7). Why every child should learn to code. The Guardian. http://www.theguardian.com/technology/2014/feb/07/year-of-code-dan-crow-songkick
Gardiner, B. (2014, março 23). Adding Coding to the Curriculum (Published 2014). The New York Times. https://www.nytimes.com/2014/03/24/world/europe/adding-coding-to-the-curriculum.html
Pérez-Marín, D., Hijón-Neira, R., Bacelo, A., & Pizarro, C. (2020). Can computational thinking be improved by using a methodology based on metaphors and scratch to teach computer programming to children? Computers in Human Behavior, 105, 105849. https://doi.org/10.1016/j.chb.2018.12.027
