Michigan K-12 AI Learning Alignment Framework — Computer Science

The Michigan K–12 AI Learning Alignment Framework maps artificial intelligence priorities to state computer science standards across four grade bands (K-12). It guides educators in teaching students how AI works, the human role in its creation, and the ethical and societal implications of the technology.

Michigan K–12 Artificial Intelligence (AI) Learning Alignment Framework – Computer Science (CS)

Contents

Introduction

The Human Role in Creating AI

Reasoning

Data in Machine Learning

Ethical Evaluation of AI Systems

Societal Impacts

AI is rapidly becoming a foundational part of the technologies students interact with every day, from recommendation systems such as book suggestions based on a user’s reading level to automated decision-making tools, like email spam filters. Helping Michigan students make sense of these technologies - how they work, how humans shape them, and how they influence society - can be supported through thoughtful alignment between AI learning priorities and the existing Michigan Computer Science (CS) Standards. The AI priorities reflected in this document are taken from the AI4K12 (Artificial Intelligence for K– 12) and Computer Science Teachers Association (CSTA) AI Priorities for All K–12 Students

Resources

References

Introduction

Glossary of Terms framework and are aligned with Michigan’s CS standards. This alignment is intended to help educators see how essential AI ideas-such as the human role in creating AI, reasoning and decision making, using data in machine learning, building AI models, evaluating ethical considerations, and understanding societal impacts-relate to the Michigan CS Standards across grade bands. Each alignment entry highlights the standard(s) that connect to the AI priority and explains how that standard may support student understanding. Additionally, suggested connections to English language arts (ELA), mathematics, science, social studies, and art illustrate how AI concepts can intersect with learning across the curriculum.

This framework can be used by Professional learning communities (PLCs) to explore where AI learning could fit within existing units and routines. Reviewing the AI priorities alongside the Michigan CS standards can help teams consider a range of possibilities for instruction, including both plugged (technology-based) and unplugged (hands-on or discussion-based) activities. The accompanying Michigan K–12 AI Learning Alignment Framework – Computer Science Data Tool offers a flexible way to filter by grade band, AI priority, standard, or instructional connection, making it easier for educators to find the most relevant information for their context. Together, this document and the Computer Science Data Tool are intended to serve as supportive planning resources that provide clarity, encourage collaborative exploration, and help educators design developmentally appropriate experiences that introduce students to AI concepts while reinforcing Michigan’s existing CS standards.

# The Human Role in Creating AI

AI systems depend on humans to design them, supply data, make decisions about their use, and evaluate when AI is or is not appropriate for a given task.

## Grade Band K–2

AI Description: Understand that AI is a tool created by humans to make decisions or to generate something (e.g., an image).

Michigan CS Standards: 1A-IC-16 – Compare how people live and work before and after the implementation or adoption of new computing technology.

Connection to CS: This standard reinforces understanding of the human role in creating AI by showing that people design technologies that change how we live and work.

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## Cross-Disciplinary Connections:

- ELA: Compare stories or informational texts about life before and after technology (e.g., “How did people communicate before smartphones?”). - Math: Use simple charts or timelines to show changes over time (e.g., number of jobs using technology now vs. then). - Science: Discuss tools humans invented to solve problems (e.g., weather prediction, medical imaging) and how AI fits into that pattern. - Social Studies: Explore historical changes in work and community life due to inventions (e.g., telephone, computer, AI). - Art: Create drawings of “before and after” scenes (e.g., a classroom with chalkboards vs. one with tablets).

# Grade Band 3–5

AI Description: Describe the roles of humans in the creation of AI.

Michigan CS Standards:

- 1B-IC-18 – Discuss computing technologies that have changed the world, and express how those technologies influence, and are influenced by, cultural practices. - 1B-IC-19 – Discuss ways in which technology can support or hinder access to information and opportunities. Connection to CS: These standards reinforce the human role in creating AI by showing that people design technologies and influence how those technologies affect access, opportunities, and society.

## Cross-Disciplinary Connections:

- ELA: Analyze informational texts on how innovations reflect human choices and cultural needs. - Math: Analyze simple datasets showing how often different technologies are used and discuss patterns in human-created tools. - Science: Investigate how scientific discoveries lead to new technologies and how humans guide their design. - Social Studies: Examine how technologies influence culture and how cultural values shape technological development. - Art: Create illustrations showing humans designing, testing, or improving a technological tool.

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# Grade Band 6–8

AI Description: Describe the roles that humans play (including in data curation and labeling) in creating and refining AI models.

Michigan CS Standards: 2-IC-21 – Discuss issues of bias and accessibility in the design of existing technologies.

Connection to CS: This standard reinforces understanding of human roles in creating AI by showing how human choices in design and data handling influence fairness and accessibility.

## Cross-Disciplinary Connections:

- ELA: Analyze texts to identify how authors choose and organize information, similar to curating data. - Math: Explore how selecting different data sets or categories changes the outcomes of a classification or graph. - Science: Investigate how scientists collect, sort, and label data during experiments and how that affects conclusions. - Social Studies: Examine how humans document, classify, and interpret information in maps, surveys, or historical records. - Art: Explore how artists choose and organize visual elements, showing how selection and labeling shape interpretation.

# Grade Band 9–12

AI Description: Evaluate and analyze the roles of humans and human decision-making in the creation of AI.

Michigan CS Standards:

- 3A-IC-24 – Evaluate the ways computing impacts personal, ethical, social, economic, and cultural practices. - 3A-IC-25 – Test and refine computational artifacts to reduce bias and equity deficits. - 3B-AP-08 – Describe how artificial intelligence drives many software and physical systems. Connection to CS: These standards reinforce evaluating human roles in creating AI by examining how human choices, values, and decisions shape computing systems and their impacts.

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### Cross-Disciplinary Connections:

- ELA: Evaluate how authors present human choices or perspectives that shape technological outcomes. - Math: Analyze how changes in data selection or weighting influence model outputs or statistical results. - Science: Investigate how human decisions in experimental design affect the reliability and interpretation of scientific models. - Social Studies: Examine how societal values, policies, and human choices shape the development and use of new technologies. - Art: Explore how intentional creative decisions influence the meaning, impact, or interpretation of visual works.

# Reasoning

AI systems must represent information about the world and then apply algorithms to reason with that information to classify, predict, or make decisions.

## Grade Band K–2

AI Description: Explain how binary choices (e.g., up/down, on/off, under/over) can be used to make decisions that lead to a specific goal by either a human or a machine.

Michigan CS Standards: 1A-AP-08 – Model daily processes by creating and following algorithms (sets of step-by-step instructions) to complete tasks.

Connection to CS: This standard reinforces reasoning with binary choices by illustrating how simple decisions guide step-by-step instructions for humans and machines.

### Cross-Disciplinary Connections:

- ELA: Write or illustrate “If–Then” stories (e.g., If it rains, then we wear boots). This reinforces conditional thinking and binary choices. - Math: Use sorting activities (e.g., sort shapes by big/small, colors by light/dark) and create simple decision trees for classification. - Science: Explore animal characteristics (e.g., Does it have fur? Yes → Mammal; No → Bird), introducing dichotomous keys. - Social Studies: Discuss everyday decisions (e.g., If the traffic light is red, then stop; if green, then go), connecting to community rules. - Art: Create visual flowcharts or “choice maps” showing steps in a process (e.g., getting dressed for different weather).

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# Grade Band 3–5

AI Description: Train a model that can make decisions based on defined criter