2022 – Scaling CS through Technology Curiosity Museum

CS – CT – CTE – Computer Technology compared:

Computer Science (CS) is about the algorithms that drive our world.  It is about AI, ML and data science.  It is about your safety as bots are now making decisions on who to kill in wars, how to sell products that market to your heart, drive cars … to name just a few things. It is about understanding coded bias and how computers communicate. It is about controlling the computer. It is about creating.

Computer Science is about the unplugged world.  It is about Computational Thinking (CT) – pattern recognition, decomposition, abstraction and algorithms. It is about learning a process to solve real world problems, to ask questions, to tell stories. It is about interconnected forces and combined operational systems. It is about building tools for the future our grandchildren face as they head into the Abyss.

Career and Technology Education (CTE) is about careers and jobs.  In Texas CS was moved to CTE to get Carl Perkins weighted funding. CTE focuses on developing skills for those who go into technical fields.  It is learning to program the software that controls computing systems.  It is about learning how to use a computer.  It is about consuming what is on our phones, using apps. CTE builds skills to be a computer scientist.

Computer Technology is about the hardware. Those who build and fix the computers, the computer engineers. All are are interrelated to build computer literacy K-12 and the mindset to become a future engineer.

Computational Thinking

2020 Data Collection so important during the search for a COVID19 cure.


2008 COMPUTATIONAL THINKING data collection site below – and growing above.

From Digital Promise and Microcredentials

– Decomposition – Abstraction – Pattern Recognition – Algorithms

Expressing an approach that a computer (human, machine or both)
can use to achieve a solution.
CT begins with an idea, a problem, a goal. A goal such as creating a video for my grandson’s 5th birthday connecting to a passion for basketball. Then connecting the dots to reach the goal using core computer science principles:

    1. Collect Data, Analyze the Data, Represent Data so Computer Understands
    2. Reduce Problem to Smaller Parts, Simplify Related Concepts to Essentials
    3. Design Algorithms – Write steps to solve a problem.
    4. Automate with Control Systems, Simulate Real World, Partner – Parallel Work

Critical Thinking + Computer Power = Computational Thinking
->>Making Decisions or Innovating Solutions

QUICK THINKING – Do you see CT components?

MORE THINKING – Was the student wrong to “break” the teacher’s rule?

All knowledge is answers to questions.  The more questions, the more knowledge. It is OK to question rules and directives. But, always follow them. Survival requires order. Success requires questions. CT builds a process to learn how to question, as a computer must be given coded rules to do anything.

Data Collection Data Analysis Data Representation
Decomposition Abstraction Algorithm & Procedures
Automation Simulation Parallelization

CT-BarefootComputingBarefootComputing – CAS UK

BBC Bitsize – KS3 CS

Each cornerstone is as important as the others. They are like legs on a table – if one leg is missing, the table will probably collapse. Correctly applying all four techniques will help when programming a computer. 

  1. A complex problem is one that, at first glance, we don’t know how to solve easily.
  2. Computational thinking involves taking that complex problem and breaking it down into a series of small, more manageable problems (decomposition). Each of these smaller problems can then be looked at individually, considering how similar problems have been solved previously (pattern recognition) and focusing only on the important details, while ignoring irrelevant information (abstraction). Next, simple steps or rules to solve each of the smaller problems can be designed (algorithms).
  3. Finally, these simple steps or rules are used to program a computer to help solve the complex problem in the best way.

Along with my math certification I earned my Computer Information Systems certification in 1985 from the University of Houston Clear Lake and my professor DrFrank@drsmatthews.net is still there. At that time programming was taught in computer math. The computer literacy MS standards in 1985 included programming. In 1989 I taught my first Computer Science course in Fort Bend ISD on an AppleIIE using Logo. I served on the first CS TEKS writing team directed by Karen Kahan and on the second draft which went to 15 courses.

I am now focusing on K5 CS Education, as I have experienced programming helps students learn math and use tools for computational thinking. This has been made easy with Blockley programming, as typing code and learning syntax is no longer needed. That ease of implementation and access to computing devices is the biggest change since Seymour Papert first used the term computational thinking in 1996. Jeannette Wing gave a speech in 2009 that brought this skill to the forefront. It is just in the last few years that this is reaching the mindset of administrators. I am in awe of what code.org has done to bring computer science to every child in one year.

Every 21st century student should have the opportunity to learn CS as the basics nurture creativity and problem-solving skills, and prepare students for any future career. Software and computers are everywhere, but less than one in ten schools teaches CS. 60% of STEM jobs are predicted to be in computer science.




  1. Origami Fold a cup or a Mini-book
  2. Plant-a-seed
  3. Create a Binary Bracelet


  1. Bee-Bot Robotics
  2. Code.org
  3. BBC Math and Literacy
  4. Teaching CT in K-5 using Robots
  5. Puzzles: Assessment, Assessment_lesson_plan
  6. TCEA Region IV Presentation

BLOGs and Articles on Algorithic Thinking I like:





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