Merge pull request #4 from chennesy/add_jargon

Author: jt14den

episodes/intro.md

@@ -58,6 +58,17 @@ Algorithms have also been criticised for bias. As Karan Praharaj [says](https://
 
 Use automation, but use it wisely, and ethically, and always with lashings of human oversight. 
 
+:::::::::::::::::::::::::::::::::::::::::  callout
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+## Jargon busting (Optional, not included in timing)
+The [Jargon Busting exercise](jargon_busting.md) is a helpful way to begin to explore terms, phrases, and ideas related to code and software development.
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+:::::::::::::::::::::::::::::::::::::::: instructor
+This exercise can be useful when you teach Computational Thinking as the introduction to a full LC workshop, especially if you want learners to have an opportunity to meet each other and interact. It can take anywhere from 10 to 45 minutes, depending on your approach.
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 #### What's next?

learners/jargon_busting.md

@@ -0,0 +1,44 @@
+---
+title: Jargon Busting
+teaching: 5
+exercises: 30
+---
+
+::::::::::::::::::::::::::::::::::::::: objectives
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+- Explain terms, phrases, and concepts associated with software development in libraries.
+- Compare knowledge of these terms, phrases, and concepts.
+- Differentiate between these terms, phrases, and concepts.
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+:::::::::::::::::::::::::::::::::::::::: questions
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+- What terms, phrases, or ideas around code, data, or software development have you come across and feel you should know better?
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+:::::::::::::::::::::::::::::::::::::::  challenge
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+## Jargon Busting
+
+This exercise is an opportunity to gain a firmer grasp on some concepts related to data, code or software development in libraries.
+
+1. Pair with a neighbor or small group and decide who will take notes.
+2. Talk for three to five minutes about any terms, phrases, or ideas related to code, data, or software development that you've come across and perhaps feel you should know better.
+3. Have the note-taker compile your list of problematic terms, phrases, and ideas.
+4. Now in a larger group (or with everyone in the workshop) spend 5 to 10 minutes working together to try to explain what some of those terms, phrases, or ideas on your list mean. You can use other people in the room/Zoom, the Carpentries' Glosario below, and other internet research to learn more about the terms.
+5. The instructor will collate terms and explanations on a whiteboard or Etherpad and facilitate a discussion about what we will cover today and where you can go for help on things we won't cover. 
+
+### [Carpentries Glosario (English)](https://glosario.carpentries.org/en/)
+While there's not a single site that will include *every* term that workshop attendees bring to the table, the Carpentries' glossary is a great starting place for computing and data science terms. [Glosario includes multilingual glossaries](https://glosario.carpentries.org/), as well.
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+- It helps to share what you know and don't know about software development and data science jargon.
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