Coding for the Future:
Looking at the Push for Computer Programming in Education
Timothy Wilson
Endicott College
At the moment, computer programming or coding is a hot topic in education. There is a high demand for computer programming technicians and a short supply (Pinkston 2015; Shein 2014), but does that mean everyone should learn to code? Learn the languages of computer programming? If so, why? What is the necessity of coding that this push from schools is rooted in? This paper attempts to answer some of these questions through looking at where we have come from and where we might go with computer programming.
A good place to start in the history of the push for computer programming in schools is the ‘space race’. The launching of the Russian Sputnik in 1957 ushered in a new era in educational reform placing high esteem in the subjects of math and science to propel us into the future. This was a new concept in education, preparing students for a world that did not yet exist (Molnar 1997). “The impossible yesterday is routine today. Wait until tomorrow.” (Loc 838), as Sir Ken Robinson (2011) states in Out of Our Minds, speaks to the recognition that change is occurring at a rapid pace, especially in technology, and it is not going to stop. Knowing this, it is critical for students to be aptly prepared for the future. This is a major theme that we are just now starting to map out the skills and aptitudes that needed or at least beneficial to preparing for the unknown social, occupational, physical existence that our students will be entering.
This unknown existence is not a new concept. No one can know the future for certain, but the distance into the future that we can more or less predict is shortening at an exponential rate. If we look at the rate of innovation for modes of communication we might start with the invention of the Gutenberg printing press in 1440. The printing press reigns for nearly 400 years before the advent of Morse Code in 1838. The gap between innovations shortens drastically then with the telephone in 1875, radio in 1885, television in 1929, fax machines in 1966, personal computers in 1977, cell phones in 1979, the World Wide Web in 1990, SMS in 1993, broadband internet in 1993, Skype in 2003, Facebook in 2004, Twitter in 2006, Snapchat in 2011 (Robinson 2011). Now I’m not saying that Snapchat is at all on par with the printing press, however, it has drastically changed the way that millennials communicate with each other, with over 100 million daily active users in 2015 (Smith 2016).
Understanding what type of coding to get into at what stage of learning to code will be critical to getting a wide range of students to develop strong understandings of what goes into developing a video game or a website. There are several different platforms and languages that have been written to be kid-friendly. What seems to be happening though is that teachers want to get their students involved with coding and choose programs that only give students a basic understanding of what programming is, not providing the practical connection from the code to the function. They are not closing that gap because the teachers themselves are untrained in technology integration, let alone computer science, and are hesitant to step into the unknown territory (Barmore 2015; Pinkston 2015; Shein 2014).
Although the term was introduced in the late 1990’s, STEM (Science, Technology, Engineering, and Mathematics) has gained in popularity and educational priority in only in the last seven or eight years, reinvigorating the political and nation-wide push for greater math and science education, as was the case with Sputnik’s launch, and recognizing technology’s importance in moving toward the future (Woodruff 2013).
In his 2009 State of the Union speech, President Obama states:
“We will not just meet, but we will exceed the level achieved at the height of the Space Race, through policies that invest in basic and applied research, create new incentives for private innovation, promote breakthroughs in energy and medicine, and improve education in math and science.”
This was the jumping point for many in the field of education. This is where the importance of STEM, now STEAM with the inclusion of arts education, received the push that we are currently seeing in American schools as well as internationally. Schools have been grabbing onto anything that has to do with technology and, seemingly, the most popular focus is on coding. However, many schools are jumping on the bandwagon without being fully prepared to follow through with the computer science or in-depth programming experiences that are needed.
Schools are generally starting off with programs that cater to beginners (it’s a good place to start), like Scratch, Gamestar Mechanic, and GameMaker or appealing to even younger students with app games like Codable (Kafai & Burke 2014; Science Buddies 2016). This is a great start and studies have shown that it is also important to introduce students to coding at an early age. They demonstrate that a great many of high school students who hold desires to pursue careers in science, math, and technology developed their interests by the age of eight and that rarely did the interests eventuate after the 7th grade (Pinkston 2015).
There are two main types of coding formats, command line (CUI), which is a text entry based format and GUI, which works by interconnecting drag and drop tiles or puzzle pieces. The original child-friendly computer language, LOGO, created by Seymour Papert and others in 1967, is in a (CUI) format while the newer platform, Scratch which was inspired by LOGO, runs in the GUI format. The advancement and major difference from LOGO to Scratch for children is in how Scratch’s snapable bricks demonstrate the constructivist’s view of learning building upon itself (Pinkston 2015; Kafai & Burke 2014). Utilizing the interlocking bricks to develop the commands for the program makes coding much more accessible to students and puts in place a strong foundation of computational concepts.
Computer programming has made its way back into the culture of education for one main reason. Digital technologies are now embedded in every aspect of our lives, in how we play, work, learn, communicate, and socialize. The creation of the kid friendly coding languages and most recently that run in the GUI format, are attempting to make it easier for children to enter and understand the world that is surrounding them (Kafai & Burke 2014)
Now, from here we can not drop the ball in during the middle school years, where many schools have sparked the interest in coding but have reached the limits of the kid friendly coding languages and games and the computational knowledge of the teachers. Currently, there are no standards set for computer science education, but there are organizations like ISTE and CSTA that have created standards that can adhered to school by school. These standards create a path toward bridging the gap between the elementary introduction to coding and the courses that some high schools offer at a higher level of computer programming (Kilfoyle Remis 2015).
According to the Bureau of Labor Statistics, the demand for computer programmers, code writers, will increase 38% just in the next two years. As well, out of the 90 million workers in the United States, 55 million of them already do some kind of programming work, mainly with databases and spreadsheets, without recognizing how the work that they are doing relates to programming (Shein 2014). With these statistics and the actuality that digital technology is all around us makes the need for including coding into schools palpable.
This whole push for coding, however, is not to train an IT army of computer programmers writing line after line of code but to develop students in many other ways as well. There are skills that have been mapped out and recognized that help students navigate this rapidly changing world. To develop these skills it is not a necessity to be able to write the code to create a video game or be a systems analyst. These skills are developed by being active computational participants.
Computational thinking teaches learners how to deconstruct a problem. It is the very nature of programming to piece together sets of commands to get a result. If the desired result is not occurring then the students need to break down the program into its components in order to determine where the problem is occurring (Shein 2014). This was the root of why Papert thought that teaching computer programming in schools was so important. He says in Mindstorms, that the “effect of strengthening the tendency to see structured analytical thinking as synonymous with good thinking.” (Gow 2015) The problem-solving skills that students develop are organic and intrinsic rather than imposed by an outside source. When students are coding, there is no one there telling them that they are wrong. Their indication that something is not right is that the output from the program does not display as they thought it would or simply does not work. When students are the ones who recognize that there is a problem, they are more likely to be inclined to seek out a solution and build on their errors (Pinkston 2015).
One of the best and most beneficial ways to learning how to code is through partnered or collaborative projects (Breed et al. 2013, Pinkston 2015). When students work collaboratively they demonstrate enhanced skills in planning, information management, monitoring and evaluation (Breed et al. 2013). Further on from working with partners, students can find many communities of practice centered around coding, whether in their local communities or online (Kafai & Burke 2014; Wenger et al. 2002).
By deconstructing problems and situations, building a working program from nothing, students gain an understanding of the world around them. When they understand what goes into the products that they use and the systems that are a play in our society they have a greater chance to participate. Dean Kamen, engineer and the inventor of the wearable insulin pump, the Slingshot water purifier, and most known the Segway has said, “Everybody has to be able to participate in a future that they want to live for. That's what technology can do.”
In researching coding education I have found a particular affinity to how Kafai and Burke frame the main aspects of computer programming education in, what they call, computational participation, as transformational components. In doing this they suggest that it is the learning processes that are most important in learning to code rather than the outcome. The four dimensions of computational participation that they outline are thus: (1) from writing code to creating applications, (2) from composing from scratch to remixing others’ work, (3) from designing tools to facilitating communities, and last, (4) from screen to tangibles (Kafai & Burke 2014). How Kafai and Burke state these four aspects of computational participation opens up my thinking about how to provide an entrance point for students. Whether that’s appealing to their interest of the intricacies of writing code or the drive to create an application that is useful, creating something from nothing or being inspired by and drawing from others work, solving a problem by designing a tool or coordinating the spread of a tool to communities that can utilize it, or utilizing the computer program to create (3D printing, engineering) or manipulate (robotics) tangible objects.
When I think about the need for everyone to learn coding I have come up with this analogy. To understand Chinese culture, do I need to learn to speak Mandarin fluently? No, I need to understand how people interact with other people and the environment. In fact, simply knowing the language will only give me glimpses into the culture, but knowing the language allows for greater access to understanding the interactions that make up the culture. Does everyone need to learn the minute details of the syntax of one or several coding languages? No, but to understand how a website or piece of software does what it does, it is necessary to understand the interactions that are occurring to make up the system. Understanding the processes that are behind the scene driving whatever software we are using provides us with the starting point for innovation. Someone who has an understanding of programming is that much more prepared to have the next innovative idea in technology, to maybe meld two existing technologies together because they know that the parts that interact will be compatible. As LEGO Papert professor of learning research at MIT, Mitch Resnick says, “In the same way that learning to read opens up opportunities for many other things, and learning to write gives you a new way to express yourself and seeing the world, we see that coding is the same way.” Learning how to code is so important, because of it’s commonplace role in everyday life, to our broadening of what fluency means in the 21st century. (Pierce 2013)
While this has not been exactly and academic research paper, the trends in the research based and non-research based articles that I have come across have solidified what I have had suspicions of, that the governmental and social pushes for the injection of coding and computer programming into education are being heeded without a real understanding of coding and computer programming by the school administrators and/or teachers themselves. Schools seem to latch onto coding programs to fulfill some requirement, whether that be governmental or social, to show “Yes, we teach coding at our school, we do things with technology.” They are doing technology for technology’s sake and failing to focus on the other benefits that learning to code and the concepts that go along with it, provide to students’ future lives. I agree with State University of New York, New Paltz adjunct education professor Jill Berkowitz who says, “Educators have a huge responsibility to be clear about why we’re teaching what we’re teaching. If a school can’t answer the question ‘Why teach coding?’ they’re not yet prepared to do it.”(Gow 2015)
As an educational technology integration specialist or as a school administrator in the future, I believe that it is my responsibility to insist computer programming is part of a child’s educational experience from the age of five or six straight on through high school and beyond. It is also my responsibility to make sure that all teachers in my organization are on the same page as to why we believe that coding education is essential and what auxiliary skills are developed from including computational thinking into the curriculum. The simplest way to do this is to adopt clear standards to follow, provide professional development time for teachers to engage with the various programming software that will be utilized in their classes, and encourage collaboration and reflection amongst staff on how the concepts of computer programming can enhance the learning in their classrooms.
References
Barmore, P. (2015) Teachers colleges struggle to blend technology into teacher training. Retrieved from http://hechingerreport.org/
Breed, B., Mentz, E., & van der Westhuizen, G. (2014). A Metacognitive Approach to Pair Programming: Influence on Metacognitive Awareness. Electronic Journal Of Research In Educational Psychology, 12(1), 33-60.
Gow, P. (2015). A NEW CULTURE OF CODING. Independent School, 74(2), 64.
Kafai, Y. B., & Burke, Q. (2014). Connected Code: Why Children Need to Learn Programming. Cambridge, Massachusetts: The MIT Press.
Kafai, Y.B., & Burke, Q. (2014). Mindstorms 2.0 Children, Programming, and Computational Participation
King, A. (2015). Reflecting on classroom practice: Spatial reasoning and simple coding. Australian Mathematics Teacher, 71(4), 21-27.
Kilfoyle Remis, K. (2015). CODING FROM KINDERGARTEN TO GRADUATION. District Administration, 51(5), 52.
Pierce, M. (2013). 21st Century Curriculum: Coding for Middle Schoolers. T.H.E. Journal, 40(5), 20-23.
Pinkston, G. (2015). Forward 50, Teaching Coding to Ages 4-12: Programming in the Elementary School. Annual International Conference On Education & E-Learning, 34-39. doi:10.5176/2251-1814_EeL15.11
Robinson, K. (2011). Out of our minds: Learning to be creative. Oxford: Capstone.
Science Buddies. (2016). Retrieved from http://www.sciencebuddies.org/science-fair-projects/project_ideas/CompSci_Kid_Programming.shtml
Shein, E. (2014). Should Everybody Learn to Code? Communications Of The ACM, 57(2), 16-18. doi:10.1145/2557447
Smith, C. (2016). By the Numbers: 70 Amazing Snapchat Statistics. DMR Stats. Retrieved from http://expandedramblings.com/index.php/snapchat-statistics/
Mathrani, A., Christian, S., & Ponder-Sutton, A. (2016). PlayIT: Game Based Learning Approach for Teaching Programming Concepts. Journal Of Educational Technology & Society, 19(2), 5-17.
Molnar, A. (1997). Computers in Education: A Brief History. THE Journal
Wenger, E., McDermott, R., & Snyder, W. M. (2002). Cultivating Communities of practice: A Guide to Managing Knowledge
Woodruff, K. (2013). A History of STEM – Reigniting the Challenge with NGSS and CCSS. NASA's Endeavor Science Teaching Certificate Project. Retrieved from www.us-satellite.net/STEMblog/?p=31
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