Bootstrap:AI invites students to explore a variety of commonly used machine learning methods, learning through hands-on applications that AI is neither mystical, nor a panacea. Rather, AI relies on geometry, functions, and statistics. The first lesson offers a framework for the remaining lessons, while the second and third lessons provide requisite computer science foundational skills.
Lesson Plans
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- Introduction to Artificial Intelligence
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Students explore the "AI effect", think about measuring similarity, and then consider characterizations of AI in popular culture.
- Simple Data Types
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Students begin to program, exploring how Numbers, Strings, Booleans and operations on those data types work in Pyret. Booleans offer an excellent opportunity for students to explore the meaning and real-world uses of inequalities.
- Contracts for Strings and Images
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Students encounter a useful representation of functions called a "Contract", which specifies the Name, Domain and Range of a function. Students learn how useful this representation is when trying to apply Functions in the programming environment, using image-producing functions to provide an engaging context for this exploration.
- Data-Driven Algorithms: Spell Checkers
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By exploring a spell checker program, students discover that AI relies on data-driven algorithms. When we provide more representative data to the computer, data-driven algorithms generally produce a higher quality output.
- Supervised Learning: Self-Driving Cars
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Students learn about the world’s first self-driving car. They then apply and extend their prior knowledge of functions within the context of artificial intelligence.
- Training Artificial Intelligence: Bags of Words
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Students consider what training is by exploring two unique examples: song recommendation and plagiarism detection. As a result of this exploration, they learn that training is the act of transforming data into a model, which is a resource-intensive and time-intensive process.
- Training Artificial Intelligence: Language in Practice
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Students explore plotting points to represent documents, data normalization, the dimensionality of language, and training the model.
- Supervised Learning: Decision Trees
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Students explore an approach to recommending videos and predicting election outcomes. They develop and analyze decision trees to predict individuals’ purchasing decisions.
- Statistical Language Modeling: Generating Text
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Students consider how statistics and probability drive AI text generation, learning that language models can produce text that sounds credible but may not actually be credible.
- Statistical Language Modeling: Chatbots
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Students consider how statistics and probability drive AI text generation, learning that language models can produce text that sounds credible but may not actually be credible.
Student Workbooks
Sometimes, the best place for students to get real thinking done is away from the keyboard! Our lesson plans are tightly integrated with a detailed Student Workbook, allowing for paper-and-pencil practice and activities that don’t require a computer. That’s why we provide a free PDF of the core workbook, as well as a link to the book with every optional exercise included.
Of course, we understand that printing them yourself can be expensive! Click here to purchase beautifully-bound copies of the student workbook from Lulu.com.
Other Resources
Of course, there’s more to a curriculum than software and lesson plans! We also provide a number of resources to educators, including standards alignment, a complete student workbook, an answer key for the programming exercises and a forum where they can ask questions and share ideas.
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Contracts Reference — Complete student-facing documentation for all the functions used in these lessons (also printed in the back of the student workbook).
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Glossary — A list of vocabulary words used in this pathway. We also provide a bilingual glossary, which defines all vocabulary words across our lessons in English and Spanish.
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Standards Alignment — Find out how our materials align with National and State Standards, as well as some of the most commonly used math textbooks.
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Teacher-Only Resources — We also offer several teachers-only materials, including an answer key to the student workbook, keys to all the exercises, and pre- and post-tests for teachers who are participating in our research study. For access to these materials, please fill out the password request form. We’ll get back to you soon with the necessary login information.
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Online Community (Discourse) — Want to be kept up-to-date about Bootstrap events, workshops, and curricular changes? Want to ask a question or pose a lesson idea for other Bootstrap teachers? These forums are the place to do it.
These materials were developed partly through support of the National Science Foundation, (awards 1042210, 1535276, 1648684, 1738598, 2031479, and 1501927). 
Bootstrap by the Bootstrap Community is licensed under a Creative Commons 4.0 Unported License. This license does not grant permission to run training or professional development. Offering training or professional development with materials substantially derived from Bootstrap must be approved in writing by a Bootstrap Director. Permissions beyond the scope of this license, such as to run training, may be available by contacting contact@BootstrapWorld.org.