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AI4K12 Grades 6-8 StandardsFoundations of Generative AI LessonsCustomizing Language Models Lessons
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CategoryBig IdeaConceptStandard12345678910112345678910111213141516
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2-A-i
Representation & Reasoning
RepresentationShow how a game board (e.g., tic-tac-toe,Chutes and Ladders, Monopoly, chess) can be represented by a description in plain language.
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2-A-ii
Representation & Reasoning
RepresentationIllustrate translation of a structure such as a game board. road map, or mind map into a labeled graph and explain the contributions of the components.
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2-A-iii
Representation & Reasoning
RepresentationDescribe the parts of a graph and how those parts are related.
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2-A-iv
Representation & Reasoning
RepresentationExplain how word embeddings (which are feature vectors) represent words as sequences of numbers.xxx
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2-B-i
Representation & Reasoning
SearchIllustrate how a computer can solve a maze, find a route on a map, or reason about concepts in a knowledge graph by drawing a search tree
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2-B-ii
Representation & Reasoning
SearchModel the process of solving a graph search problem using breadth-first search to draw a search tree.
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2-C-i
Representation & Reasoning
ReasoningCategorize problems as classification, prediction, combinatorial search, or sequential decision problems.
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2-C-ii
Representation & Reasoning
ReasoningCompare several algorithms that could be used to solve a specific type of reasoning problem
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3-A-iLearningNature of LearningContrast the unique characteristics of human learning with the ways machine learning systems operate.xx
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3-A-iiLearningNature of LearningModel how unsupervised learning finds patterns in unlabeled data.x
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3-A-iiiLearningNature of LearningTrain and evaluate a classification or prediction model using machine learning on a tabular dataset
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3-A-ivLearningNature of LearningExplain the difference between training and using a reasoning model.
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3-A-vLearningNature of LearningCompare how a decision tree learning algorithm works vs. how a neural network learning algorithm works.
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3-A-viLearningNature of LearningExplain the differences between supervised learning and reinforcement learning.
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3-B-iLearningNeural NetworksIllustrate the structure of a neural network and describe how its parts form a set of functions that compute an output.xx
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3-B-iiLearningNeural NetworksDemonstrate how a learning rule can be used to adjust the weights in a one-layer neural network.x
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3-C-iLearningDatasetsCreate a dataset for training a decision tree classifier or predictor and explore the impact that different feature encodings have on the decision tree.
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3-C-iiLearningDatasetsIllustrate how objects in an image can be segmented and labeled to construct a training set for object recognition.
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3-C-iiiLearningDatasetsExplain how the choice of training data shapes the behavior of the classifier, and how bias can be introduced if the training set is not properly balanced.
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4-A-iNatural InteractionNatural LanguageDemonstrate a computer's grasp of grammar by using a parser program to display the syntactic structure of a sentence, and explain what the nodes represent
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4-A-iiNatural InteractionNatural LanguageIllustrate how understanding a sentence could be challenging for a computer by giving sentences where a prepositional phrase could attach in either of two paces, and show how this ambiguity can sometimes be resolved based on meaning.
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4-A-iiiNatural InteractionNatural LanguageIllustrate how word embeddings can be used to reason about the meaning of words.'xxx
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4-A-ivNatural InteractionNatural LanguageDescribe some NLP (Natural Language Processing) tasks computers can perform, and explain how they work.
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4-B-iNatural Interaction
Commonsense Reasoning
Explain the knowledge a computer would need to solve a naive physics reasoning problem.
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4-C-iNatural InteractionUnderstanding EmotionDescribe how computers use different types of cues to recognize human emotional states.
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4-D-iNatural InteractionPhilosophy of MindDefine criteria for consciousness and evaluate AI systems or fictional AI characters according to those criteria.
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5-A-iSocietal ImpactEthical AIEvaluate the ways various stakeholders' goals and values influence the design of AI systems.xxxxxxxxx
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5-A-iiSocietal ImpactEthical AIEvaluate how an AI system meets the design criteria of accountability and respect for privacy.
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5-A-iiiSocietal ImpactEthical AIEvaluate ways that AI system designers can learn about and incorporate the values of their stakeholders into the design process.xxxx
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5-B-iSocietal ImpactAI & CultureExamine an aspect of daily life that is predicted to change due to the introduction of AI technologies.xxxxxxxxxx
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5-B-iiSocietal ImpactAI & CultureCritique uses of AI technology that can be used to surveil people or violate their privacy.
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5-C-iSocietal ImpactAI & the EconomyCompare the changes AI is bringing to society with those of previous industrial revolutions.
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5-C-iiSocietal ImpactAI & the EconomyPredict a new type of job that might arise, or how an existing type of job might change or go away, as a result of the adoption of AI technologies.
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5-D-iSocietal ImpactAI for Social GoodCreate a novel application using some of the AI extensions or plugins available in the programming framework of your choice.
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5-D-iiSocietal ImpactAI for Social GoodResearch a societal problem and describe how AI technologies can be used to address that problem.xxxx