Teaching Kids to Code (When You're Not Quite Sure How to Code Yourself)

by Stacy Bressette

Return to: ETAP 623 Spring 2020 (Zhang) | Mini-Course front page template

This is a screenshot of a game I built in Scratch!

My Topic and Purpose

My course will guide teachers through introducing coding and computational thinking lessons to students in their classrooms, even (and especially) when they have very little experience themselves.

Intended Audience

While I hope my mini-course will prove useful for a wide range of learners, this mini-course is designed for K-12 educators with little or no experience in learning or teaching computer science. Further, this course is designed to facilitate the incorporation of technology into existing lessons and curricula to enable teachers to provide their students with learning opportunities in digital literacy and computer programming without having to displace other learning goals, since teachers are under heavy requirements to meet curriculum standards for a wide spectrum of educational subject areas.

Learning Outcomes

After completing this mini course, learners will be able to:

  • Explain the four components of computational thinking and give both digital and unplugged examples.
  • Implement unplugged activities and strategies for developing their students' computational thinking skills in the classroom.
  • Explain basic programming concepts, including variables, loops, functions, conditional statements, comparison operators, data types, and algorithms
  • Build their first projects in MIT's Scratch platform.
  • Support students developing self-efficacy and independence as they learn to test and trouble-shoot their projects.

Curriculum Map

Screen Shot 2020-04-30 at 10.00.35 PM.png

Module One: Why Teach Coding?

  • Coding teaches fundamental problem-solving, critical thinking skills, and tenacity that will help students regardless of what they do after their K-12 education is finished.
  • Learning to code provides students with the skills they need to compete in the modern workforce.
  • New curriculum standards have been provisionally accepted by the NY Board of Regents for initial implementation in Fall of 2023.

Module Two: Computational Thinking and How to Teach It

  • The four components of Computational Thinking:
   1) Decomposition
   2) Pattern Recognition
   3) Abstraction
   4) Algorithms
  • Unplugged activities
  • Digital activities

Module Three: Coding to Learn and Learning to Code

  • What is it actually like to code?
  • What is it like to learn to code?
  • Some fundamental coding concepts
  • Your First Scratch Project
  • Troubleshooting (on your own and with students)
  • Peer collaboration
  • Building student self-efficacy

Module Four: Integrating Coding Lessons into the Curriculum

  • Coding as a Tool Set (Not a subject!)
  • Coding as Creativity
  • Coding as Authorship
  • Putting Math into Action
  • A Classroom Full of Teachers

Module Five: Reflections and Next Steps

  • The Best Answer You can Give
  • "Failing" to Create Safe Space
  • A Classroom Full of Teachers, Part II

To get started, click here: Module One: Why Teach Coding?

References and Resources

Ajwa, I. (2007). Preparing future secondary computer science educators. American Secondary Education, Vol. 35, No. 3 (Summer 2007), pp. 54-62. Retrieved from: https://www.jstor.org/stable/41406089.

Be My Eyes. Our story. Retrieved from: https://www.bemyeyes.com/about

Bressette, S. Computational Thinking RPG. TechnicallyStacy.com. Retrieved from: https://technicallystacy.com/projects/computational-thinking-rpg/

Computer History Museum. Timeline of Computer History. Retrieved from: https://www.computerhistory.org/timeline/software-languages/

Dastin, J. (2018). Amazon scraps secret AI recruiting tool that showed bias against women. Reuters, October 9, 2018. Retrieved from: https://www.reuters.com/article/us-amazon-com-jobs-automation-insight/amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK08G

Harrison, S. Five years of tech diversity reports - and very little progress. Wired. October 01, 2019. Retrieved from: https://www.wired.com/story/five-years-tech-diversity-reports-little-progress/

Krauss, J. & Prottsman, K. (2017). Computational Thinking and Coding for Every Student. Thousand Oaks, CA: Corwin.

Lauwers, G. (2019). Reshaping teacher training to get the right education system for a knowledge society. In Kowalczuk-Waledziak, M., Korzeniecka-Bondar, A., Danilewicz, W. and Lauwers, G. (Eds.), Rethinking teacher education for the 21st century: Trends, challenges and new directions. Retrieved from: https://www.jstor.org/stable/j.ctvpb3xhh.7.

Fact Sheet 18-6 Certification in Computer Science Source: NYSUT Research and Educational Services. Retrieved from: http://www.nysut.org/resources/all-listing/research/fact-sheets/fact-sheet-certification-in-computer-science.

Flamm, M. (2018, March 27). New York will finally have certified computer science teachers. Crain's New York Business. Retrieved from: https://www.crainsnewyork.com/article/20180327/NEWS/180329893/new-york-will-finally-have-certifiec-computer-science-teachers.

Fluck, A., Webb, M., Cox, M., Angeli, C., Malyn-Smith, J., Voogt, J., and Zagami, J. (2016). Arguing for computer science in the school curriculum. Journal of Educational Technology & Society, Vol. 19, No. 3 (July 2016), pp. 38-46. Retrieved from: https://www.jstor.org/stable/10.2307/jeductechsoci.19.3.38.

Marji, M. (2014). Learning to Program with Scratch. San Francisco, CA: No Starch Press.

Martin, N. (2019). Google's artificial intelligence hate speech detector is 'radically biased,' study finds. Forbes, August, 13, 2019. Retrieved from: https://www.forbes.com/sites/nicolemartin1/2019/08/13/googles-artificial-intelligence-hate-speech-detector-is-racially-biased/#40d90d7b326c

New York State Education Department. (2020). Draft New York State computer science and digital fluency learning standards: Grades K-12. Retrieved from: http://www.nysed.gov/curriculum-instruction/computer-science-and-digital-fluency-learning-standards.

Pfeiffer, W. M. (2019). There are 700,000 open tech jobs in the US. Here is how companies can fill them. CNBC, June 19, 2019. Retrieved from: https://www.cnbc.com/2019/06/18/there-are-70000-open-tech-jobs-here-is-how-firms-are-hiring-for-them.html

Scratch. Scratch for Educators. Retrieved from: https://scratch.mit.edu/educators

Shein, E. (2019). Tech jobs will see steady growth through 2023. TechRepublic, December 19, 2019. Retrieved from: https://www.techrepublic.com/article/tech-jobs-will-see-steady-growth-through-2023/

Silberstein, R. (2019, October 31). Siena College first in New York to certify computer science teachers. Albany Times Union. Retrieved from: https://www.timesunion.com/news/article/Computer-science-teacher-certification-comes-to-14655906.php.

Yang, Y-T. C., Chao-Hsiang, C. (2013). Empowering students through digital game authorship: Enhancing concentration, critical thinking, and academic achievement. Computers & Education, 68(2013), p. 334-344. Retrieved from http://dx.doi.org/10.1016/j.compedu.2013.05.023