Busting Curricular Myths of Teaching Python

As teachers of Python, we constantly strive to engage as many learners as possible with meaningful projects and examples to hook and help students make connections with coding. We carefully hone our lesson plans and activities to make them more exciting and effective each time we teach them. We measure our successes based on how many learners engage out of the entire group. But are we collecting the right data to measure success? What happens when we only reach the same type of learners with each project or example? How many potential Python programmers are we missing because they don’t connect with the material we are presenting?

Python is one of the most versatile programming languages, beloved by the most diverse and welcoming communities. How can we broaden the beginners’ learning platform to develop examples and projects to meet the needs of every student? Let’s bust some myths about the perfect curriculum!

Transcript

1. TEACHING
   Sean Tibor
   AN EDUCATIONAL PODCAST
   Kelly Paredes
   With Kelly & Sean
   PYTHON
   

   View Slide

2. 2
   www.teachingpython.f
   m
   Busting
   Curricular Myths
   Teaching Python
   PyCon Education Summit 2022
   2
   www.teachingpython.fm
   

   View Slide

3. 3
   www.teachingpython.f
   m
   OUR
   JOURNEY
   3
   www.teachingpython.fm
   

   View Slide

4. 4
   www.teachingpython.f
   m
   All kids love games, so every student should build games
   to start learning Python.
   Myth 1: Everyone Loves Games
   

   View Slide

5. 5
   www.teachingpython.f
   m
   Our Experience:
   ● Games
   ● Word Puzzles
   ● Math Problems
   ● CircuitPython
   ● micro:bits
   ● Turtle()
   ● YouTube makeup artists
   ● Interactive storytelling
   ● “Cheating” on middle school
   physics homework
   ● Computer vision
   ● Machine Learning
   ● Web scraping
   ● Twilio API
   ● Codebreaking
   ● Ethical Hacking
   ● Finance and Bitcoin
   ● Robotics
   ● Data analysis
   ● Graphing and visualization
   ● Social Entrepreneurship
   ● Treasure Hunts
   ● Language Translation
   ● Telecommunications
   ● Home automation
   ● Music composition
   

   View Slide

6. 6
   www.teachingpython.f
   m
   Student projects should be directly comparable
   to one another for fairness in grading.
   Myth 2: Producing Products
   

   View Slide

7. 7
   www.teachingpython.f
   m
   Our Experience:
   ● Process Art versus Product Art
   ● The best learning comes from student agency and choice
   ● Embrace the chaos of student-selected projects
   ● Make your rubrics reflect real learning (they’re subjective anyway)
   ● Process produces creativity; product produces only one “right”
   way.
   ● The final work product matters more to the student than it does to
   the teacher
   

   View Slide

8. 8
   www.teachingpython.f
   m
   The Points Don’t Matter
   But the Learning is Real
   

   View Slide

9. 9
   www.teachingpython.f
   m
   Trivial examples work best for communicating concepts.
   Myth 3: #FooBar4Ever
   

   View Slide

10. 10
    www.teachingpython.f
    m
    Our Experience:
    ● Metaphors help create connections; hard to connect to “non” words.
    ● Students spend more mentally energy deciphering words than
    deciphering concept.
    ● The amount and quality of prior knowledge influence new
    knowledge acquisition and the ability to apply higher order thinking
    to solve problems.
    ● Language can be exclusive or inclusive, focus on teaching for all
    children.
    ● Support PEP8
    

    View Slide

11. 11
    www.teachingpython.f
    m
    Jaime Escalante
    Ask, ‘How will they learn best?’
    not ‘Can they learn?’
    11
    www.teachingpython.fm
    

    View Slide