ITP AI Guidelines
Learning Objectives
In this workshop we will build understanding in, discuss, and ask questions around how we use AI during the ITP and how we prioritise learning.
Context: Understanding is more important than productivity (5 mins)
Learning a new computing language is not a quick task, and software engineering practices are not going to immediately make sense. At The Docs, our focus is on cementing good quality foundational understanding and building on those foundations as you progress through the course and across courses.
Building understanding is why we:
- Prioritise feedback at all times with demos, pair programming, mock interviews, and pull request code reviews etc.
- Avoid giving answers and instead ask more questions when you have blockers in your work.
- Run Checkpoint before people can progress to SDC.
- Build up your knowledge from fundamental HTML+CSS, into JavaScript, and then into wider and deeper computer concepts in the SDC.
AI: A predictive word-generator
Quick round of defining terms
As a class, can you call out definitions of the following terms (definition is in the toggle, don’t reveal early!):
LLM
Large Language Model - deep learning model trained on huge data sets. Can understand and generate human language content.Prompt
The input given to a LLM, commonly in the form of AI assistants.AI Chatbot (+examples)
Software application using LLMs + genAI to take a user's prompt and generate human language responses. Examples include ChatGPT, customer assistance AI bots, Claude etc.AI chatbots are often LLMs. LLMs are “trained” on huge amounts of data to predict what word should come next in a sentence. Because they can read and generate text data, it feels like you’re messaging a smart “person”, but it is just software that has an algorithm for guessing what words should follow your prompt.
AI can be the tempting shortcut
It can be easy for AI tools to do the hard work for us, e.g. solving the problem, fixing errors, or even writing emails for us. When AI does the work for us, we may think we’re making progress and learning when we’re not.
- We’re actually not building skills that will make us employable.
- We’re not understanding why we do certain things and what happens when we do them incorrectly.
We need to do that work ourselves, so that we build the deeper skills that will help us in our careers.
Read through our ITP AI use guidelines and discuss (15 minutes)
Individually, for 5 minutes read through the guidelines for AI use on the ITP.
After the 5 minutes is up, set another timer for 5 minutes. As groups (3 - 4 people) discuss the following questions:
- What general skills are we trying to build during the ITP (which of these could using AI chatbots disrupt)?
- What is an example of acceptable AI use?
- Which kinds of AI use are not acceptable during the ITP?
There might be multiple different approaches to the questions. Discuss and see if there is agreement across the group.
Set a timer for 5 minutes and as a entire ITP class popcorn around the different groups and get one answer for each of the questions. Specifically looking for any big misconceptions across the class.
What questions do we have (10 minutes)
Facilitator should start a Slack thread for your region within the ITP channel. Everyone should use this thread to post any questions about AI use that they have. Take the remaining time to address these questions.
As a region, it might be worth feeding back to the ITP channel any big misconceptions that were repeated across the group. This could be something more people are unclear about across the ITP and it can be addressed in the wider channel.
Stretch: Find the wider AI usage guidelines (5 minutes)
If you have time to spare, spend 5 minutes in pairs navigating the curriculum to find the “AI Usage Guidelines” in the CYF Guides. When you’ve found it, answer the following question:
What question can you ask yourself to check if you are using AI appropriately?