Participate and share: Interactive session 
Purpose: To empower participants to teach their students about programming with real-world software engineering tools through the development of a computer vision program.
Objectives:
Participants will be able to guide students on the use of a Large Language Model (LLM) to generate, debug, and edit software program code.
Participants will be able to explain and demonstrate the use of Git and GitHub for facilitating student collaboration on software development.
Participants will be able to understand the challenges in training and incorporating a computer vision model into a software program.
Participants will be able to explain how they might adapt these lessons and activities best to meet the needs of their schools and students.
Evidence of Success:
Attendees will leave the session with artifacts they created, including code they wrote, with the assistance of an LLM and a computer vision model they trained and tested themselves.
Attendees will report that their confidence in teaching these skills and concepts to their students increased as a result of the session.
Attendees will share specific ideas of how they plan to adapt these lessons to meet the needs of their situation best.
Warm Up (5min) - Think-pair-share for participants on experience with topics covered in the session: Version-Control Software, Programming with AI Tools, and Computer Vision
Module Overview (5min) - Presenter will walk through the sequence of lessons and activities contained in the module using slides
Classroom Data (5min) - Presenter will show both quantitative and qualitative data collected from classrooms using this module via slides
Scavenger Hunt (10min) - In pairs, participants will work on an activity from the curriculum in the form of a scavenger hunt that walks through some of the basics of Git and GitHub
Pair Programming with CoPilot (15min) - Presenters will model programming with an large language model acting as a driver and as a navigator. Then, participants will get a chance to try themselves.
Train Your Own Model (10min) - In pairs, participants will train a model using the website Teachable Machine. Share out of successes and challenges to end this section.
Wrap Up (10min) - Present some example student projects, provide ideas from teachers on how to adapt this module, discuss with participants how they might use these lessons in their classroom
Studying the effect of AI Code Generators on Supporting Novice Learners in Introductory Programming
https://arxiv.org/pdf/2302.07427.pdf
Github copilot in the classroom: learning to code with AI assistance
https://dl.acm.org/doi/abs/10.5555/3575618.3575622
How Novices Use LLM-Based Code Generators to Solve CS1 Coding Tasks in a Self-Paced Learning Environment
https://arxiv.org/pdf/2309.14049.pdf
Teaching CS-101 at the Dawn of ChatGPT
https://dl.acm.org/doi/10.1145/3595634
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