The different roads we take (Tracy Osborn)

• Talks are concrete, focused, conclusions,
• Keynotes give exposition for a topic, start conversation.

My rocky road to CS

• Liked computers but prefer doing visual stuff.
• Lots of HTML, web pages.
• Went to study CS, but it all sounded like Chinese.
• Java wasn't really for me...
• But the GUIs really made sense.
• Abstract concepts didn't make sense at all despite all effort.
• The professor said that I was lazy and I left CS and did an Arts degree.
• I became a Frontend developer but avoided JavaScript since it has the world "Java" in it.

In the bigger picture

• Women amond CS graduates:
  • 1985 37%
  • now 17%
• Percentage of women in CS-related professions also declined.
• The introductory book was renamed from Intro to Symbolic Programming to The Beauty and Joy of Computing, same year women in class outnumbered men.
  • The new coursebook sounds much more wide (whatever that means).
• Tried to found a startup (WeddingType) but didn't find a technical co-founder.
• Django is awesome, it hides all the complicated details.
  • Made the weddingtype app in 6 weeks.
  • Wrote Hello Web App book to help people build web apps.
    • Tailored to visual learning style.
  • Taught workshops for beginners.
• Recurse center: was hard to program something without Django, but not too bad.
• "One true programmer myth" is harmful for diversity.

• We should be more acceptable of people who took a different path from us, or a non-traditional path.
• We should celebrate the different ways that people use to learn programming.
• Ultimately, everyone is self-taught, it's just that some people also have a CS degree.

• Simple frameworks and bootcamps increase the pool of people who can get into the field. It gets more diverse and that makes our community stronger.
• Not all beginners want the same thing (e.g. depth vs breadth).

Action points

• Reject "one true programmer".
• Embrace the mediocre programmer (talk by Jacob Kaplan-Moss, PyCon 2015).
  • https://www.youtube.com/watch?v=hIJdFxYlEKE
• Don't classify things into beginner / intermediate / advanced.
  • Beginnner + Deployment,
  • Intermediate + Data Science.
• Mentor!
• Assess "what am I good at / what am I bad at".
• Build more tutorials, guides.
• You can teach even if you feel as a "beginner".
  • Experts sometimes make bad teachers because they forget how it felt to not understand these things.