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4.4 Investigating LLMs

In this lesson, students interact directly with several LLMs to evaluate model performance and think critically about implications of model output for their work, their peers, and for society.

In this lesson, students interact directly with several LLMs to explore differences in model output and performance. Through a guided investigation of LLM responses to different prompts, students learn that LLM output is 1) a probabilistic (answers are different nearly every time) and 2) not based on ground truth. They also learn to build different prompts or prompt frameworks for different purposes.

4.2 Fine Tuning

In this lesson, students do not use LLMs. Instead, then engage in playful, hands-on/unplugged activities that focus on the crucial stage of fine-tuning LLMs, highlighting the human influence on their behavior and output.

4.1 Pre-training

In this lesson, students do not use LLMs. Instead, then engage in playful, hands-on/unplugged activities that aim to demystify how LLMs learn language by exploring concepts like tokenization, vectors, and attention mechanisms. It consists of three activities, each building upon the previous one.

4.0 Intro to LLMs Lesson

In this lesson, students ≥13 use LLMs (i.e., chatGPT, Gemini, etc.) (teachers demo for students <13) to engage in a series of investigations that reveal how different LLMs can output misleading and/or biased information. By exploring and discussing these limitations, learners realize that biased output can be the result of patterns from the data, “hard-coded” or programmed directives from the developers, or personal bias.

Unit 4: Introduction to Large Language Models (LLMs)

This unit explores Large Language Models (LLMs) by focusing on the interplay between prompts and generated output. It uses a "hands-on" approach, employing unplugged games and simulations to demystify core LLM concepts.

Career Exploration and Impacts of AI Lesson plan with print Worksheet and Google Form Exit Ticket

Career Exploration and Impacts of AI for post secondary training, 2 year and 4 year degrees. Emphasis on continuing training or traditional education in STEAM careers whether it be an apprenticeship, certificate program, 2 year college, 4 year university or beyond. Emphasis on AI impacts in all fields. Combined Inventory of Me, AI’s Impact, and Roadmap to My Dream Job into a WS (2-3 day portfolio-like). They fill it in along with slides as they go.

Investing Bias in AI- Including Immigration Facial Recognition Apps

Investigating Bias including Immigration Facial Recognition Apps

Added in an example of facial recognition bias for asylum seekers. This change was designed for my students, part of who herald from immigrant families and who have darker skin colors. Immigration is a very important topic so adding this slide adds to the relevance of their lives and will help them internalize the information. This change is relevant for teachers that teach in states close to national borders and communities with large immigrant populations.

Best Bocadillo

Making the best sandwich instead of PB & J for those who have not experienced PB & J. The reason I made this change is because there is a large Hispanic population in my area who do not make sandwiches with peanut butter and jelly and so a sandwich in general is more relevant to students of diverse populations such as Latinx, Asian, etc.

Ethical Matrix Lesson for Food Deserts

High school (HS)Students: Use ‘Teen’ instead of ‘Child’ Added ‘Store’ instead of ‘Doctor’ Teachers can talk with their students about topics relevant to their lives like: a)workers in the store; b)food available in local stores; c)accessibility of local stores; d) impact on people, supplies, and accessibility of stores

Generate A Story

Adust lesson to authors to reflect their areas/regions/states. This modification was designed to build Culturally Relevant elements into the AI curriculum.

PSA on Spread of Misinformation

Students will create a PSA presenting the problems with the Spread of Misinformation.

Neural Network Escape Room

Students will create an escape room on google slides that teaches neural networks. (To be done after teaching the Neural Network lesson)

I am from poem

This lesson student will create an “I am from Poem”. This is an introduction lesson to get to know your students and to start building relationships. Building positive relationships is the foundation for motivating students to want to learn. It shows students that respect their opinions and interests.

Teachable Machine: Geology-- Rock Classification

Students will create a supervised learning model that will classify igneous, metamorphic, and sedimentary rocks.

Teachable Machine: Classifying Cells

Using Teachable Machines to classify cells as prokaryotes or eukaryotes.

What is AI? Kahoot Teacher Made

This Kahoot series can be used in situations where students need to independently complete the introductory "What is AI?" (0.1) lesson, such as before a workshop that focuses on a specific AI tool. It walks them through the slides to learn about AI, and then practice distinguishing technologies that are AI from ones that are not AI, including explanations for each. Students can complete the "advanced" slides after they do the "introduction" ones, to get more practice.

AI or Not ? Teacher Made

This is a modified Version of the AI or Not resources to include some more current and student friendly images.

What to Ponder as you Journal about AI

A little direction for students before and after they learn about the AI topics throughout the DAILy Curriculum.

Search for "[keyword]" across the whole site.

Everyday AI