Teaching Scala - A Roundtable Discussion
summary
Panelists compare concrete training practices and pain points: a company-scale onboarding of 30 hours of training backed by full-time instructors, community-run Scala Bridge classes for newcomers, and universities using Scala for CS1/CS2 and a MOOC. Tools and gaps include heavy use of millions of lines of Scala in production, Spark/scalding for data pipelines, scarce tutorials for higher-kinded types, weak plotting libraries for data science, and an optimism that Scala 3’s baby algebraic effects will ease effect composition.
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chapters (30)
- 0:00Introduction
- 1:10Heather Miller
- 2:07Marc Lewis
- 2:28Ryan Tanner
- 3:00Pasha Gurupada
- 3:21How do you help newcomers understand Scala
- 4:38Twitters Scala training program
- 5:51What can other companies do
- 6:08Teaching students with Scala
- 9:07Teaching students with Racket
- 11:27Teaching Scala in academia
- 13:06Teaching Scala in the industry
- 15:13Keeping material accessible to newcomers
- 15:50How to bridge the gap
- 16:53Introducing category theory concepts
- 20:01Scala styles
- 21:13Scala the right way
- 24:31Lack of accessible tutorials
- 26:35Lack of experience teaching
- 27:27Lack of accessibility
- 31:28Scala Bridge
- 34:12Two Types of Students
- 34:45Motivation
- 37:22Types
- 38:41Python vs Scala
- 40:57Big Data
- 41:50Prescreening
- 42:39Why Scala vs Java
- 43:32Java vs Scala
- 44:33Final Thoughts
