Montana Artificial Intelligence in K-12 Education Guidelines (v1.0, October 2025)

The Montana Artificial Intelligence in K-12 Education Guidelines aim to help Montana school districts integrate AI responsibly. This living document will be updated biannually, focusing on equitable access and robust data privacy for all students.

# Montana Artificial Intelligence in K12 Education Guidelines

## Prepared for Montana educators, administrators, families, and policymakers

Version 1.0 \| October 2025 \| Biannual Review Cycle \| Feedback Invited via frontierlearninglab.io/feedback

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Welcome and Acknowledgements

The Montana Artificial Intelligence in Education Guidelines are designed to support district leaders in creating and refining implementation guidance as well as developing AI-related policies. Grounded in Montana’s educational vision, this document provides a foundation for developing local guidance and policies, while training educators to responsibly integrate AI tools, strengthen AI literacy, and build adaptive systems that evolve with emerging technologies.

The Montana Office of Public Instruction (OPI), in collaboration with the Frontier Learning Lab at the Montana Digital Academy and key education partners, is leading the development of this guidance for district leaders across Montana. We extend our gratitude to all those who contributed to this drafting process. In concert with this effort, the Montana School Board Association is releasing model policies to school boards and districts across the state.

This work reflects Montana’s unique context, serving rural, urban, and tribal communities. Together, we are moving forward to support the safe, ethical, and equitable integration of AI in education, with a focus on achieving enhanced outcomes and expanding opportunities for all students.

Thank you for your partnership,

Susie Hedalen

Superintendent of Public Instruction

Jason Neiffer

Executive Director, MTDA

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# TABLE OF CONTENTS

## Welcome and Acknowledgements ... 2

## TABLE OF CONTENTS ... 3

## Introduction ... 4

## Core Principles for AI Use in Montana Schools ... 5

## Benefits and Risks of AI in Education ... 6

Benefits ... 6 Risks ... 6 **AI in Teaching and Learning ... 7** Integration with Curriculum ... 7 Ethics, Safety, and Societal Impact ... 7 Creativity, Collaboration, and Critical Thinking ... 8 Family & Community Engagement ... 8 Innovation ... 8 **Professional Learning for Educators ... 9** Guiding Principles ... 9 Recommended Practices ... 9 **Accessibility ... 10** Guiding Principles ... 10 Recommended Practices ... 10 **Data Privacy and Security ... 11** Guiding Principles ... 11 Recommended Practices ... 11 **Policy and Governance ... 12** Constitutional Players ... 12 Tribal Sovereignty and Consultation ... 12 Local Control and Rural Realities ... 12 Governance Practices for Districts ... 13 Higher Education/Workforce Connections ... 13 Student and User Data Privacy ... 13 **Implementation Roadmap ... 14** Capacity Building Supports ... 14

I. Establishing a Strong Foundation and Vision ... 14 II. Developing Policies and Practices for Responsible Use ... 15 III. Capacity Building and Professional Learning ... 15 IV. Accessibility and Implementation Pathways ... 15

V. Monitoring, Evaluation, and Continuous Improvement ... 16

## Glossary ... 17

## References ... 18

State Guidance Documents ... 18 National and International Resources ... 18 Montana Constitutional and Statutory Anchors ... 19 How AI Supported the Development of this Document ... 20

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# Introduction

This guidance is designed to support Montana’s schools and districts as they explore and implement Artificial Intelligence (AI) in K–12 education. It is a living document, reviewed and updated biannually and refined as technologies, policies, and classroom practices evolve. Feedback is welcome to ensure this document remains practical, relevant, and responsive to Montana’s unique educational landscape.

To keep this work responsive, districts, educators, parents, and students are encouraged to share feedback via frontierlearninglab.io/feedback. We will gather input annually, and updates will be published with explicit versioning.

AI presents both opportunities and challenges. These guidelines are designed to help districts make informed, locally relevant decisions.

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# Core Principles for AI Use in Montana Schools

To help anchor local policy and implementation, it is recommended that districts adopt the following principles, supported by professional development resources and clear implementation guidance tailored to each district.

## Data Privacy & Security

AI use should comply with all relevant laws and policies related to student data, including FERPA and COPPA, and uphold strong data governance practices. Students and families should be protected from unnecessary surveillance, data sharing, or automated decision-making without consent.

## Transparency & Accountability

AI tools must be explainable and understandable. Educators, students, and families deserve to know when AI is involved in learning, grading, decision-making, or access to services.

## Bias Awareness & Information Verification

AI tool outputs must be critically examined for embedded biases and the accuracy of the information they produce. Districts should regularly assess protocols to mitigate harms caused by bias or unverified information.

## Human Oversight & Educator Judgment

AI should support, but not replace, educators. Teachers bring context, empathy, and moral reasoning that no machine can replicate. All AI use must include active human engagement and oversight.

## Academic Integrity

AI must be used in ways that reinforce learning, not undermine it. Clear expectations should guide when and how students use AI tools, with an emphasis on originality, transparency, and reflection.

Districts and schools are encouraged to seek out professional learning opportunities and vetted implementation resources to support these principles in practice. Districts are encouraged to consult MTSBA’s model policies as they operationalize these principles within board-approved frameworks, as well as exemplar district policies from other Montana school districts through the Frontier Learning Lab.

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# Benefits and Risks of AI in Education

Artificial Intelligence presents a range of transformative opportunities for K–12 education, accompanied by significant challenges that necessitate thoughtful navigation. Montana’s districts should approach AI adoption with a balanced lens—seeking benefits where they align with instructional and district goals while remaining aware of potential harms.

## Benefits

- **Personalized learning and tutoring: AI tools—such as adaptive tutoring systems—can tailor instruction to** meet the individual needs of students and support those from under-resourced backgrounds. - **Enhancing educator capacity: AI can streamline routine tasks, such as lesson planning, generating materials,** and monitoring student progress, thereby reducing the administrative load. This allows teachers to devote more time to higher-order work—fostering critical thinking, nurturing creativity, supporting social-emotional learning, and building meaningful connections with students—while maintaining human oversight and accountability. - **Accessibility enhancements: AI-powered tools (e.g., text prediction, translation, voice-to-text) enhance access** for students with disabilities or those with language needs. - **Simulated and real-world learning: AI enables immersive simulations and the exploration of real-life** scenarios, bridging classroom learning with practical applications that align with workforce skills.

## Risks

- **Bias and misinformation: AI tools can reflect biased data or provide inaccurate outputs.** - **Overreliance and erosion of learning processes: Students depending too heavily on AI may bypass critical** thinking and the deeper learning that comes from productive struggle. - **Erosion of interpersonal skills: Excessive AI use can reduce face-to-face interaction and social-emotional** development, particularly in younger learners. - **Access gaps: Without adequate infrastructure, AI could exacerbate digital divides—leaving rural or financially** constrained districts behind. - **Privacy and surveillance concerns: AI-powered monitoring or data-heavy tools (such as assessment** platforms) raise risks if data is mismanaged or a breach occurs. - **Ethical complexity for children: AI’s impact on learning values is complex and demands careful, intentional** design.

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AI in Teaching and Learning

The integration of AI into education is an accelerating phenomenon with profound implications for human thinking, interaction, and decision-making. This guidance advocates for a human-centered approach to AI, emphasizing that AI should serve to strengthen human capabilities and contribute to accessible, just, and sustainable futures, rather than undermining human intelligence, agency, or the fundamental human-to-human relationships that are vital in education. This approach ensures that AI enhances, rather than diminishes, the educational experience.

Integration with Curriculum

● Developmentally Appropriate: AI integration should be thoughtfully planned across subjects and grade levels in age-appropriate and progressively scaffolded ways. This progression should account for students' cognitive and emotional development, especially their ability to critically evaluate AI outputs. ● Reinforcing Core Content and Digital Literacy: Integrating AI in education must be built upon a strong foundation

● Reinforcing Core Content and Digital Literacy: Integrating AI in education must be built upon a strong foundation of foundational literacies, including basic literacy, numeracy, coding, and media and information literacy. These are considered essential for navigating and shaping the AI era. AI concepts should be integrated interdisciplinarily across various subjects, such as science, technology, engineering, arts, and mathematics (STEAM), as well as social studies, world languages, humanities, and civic education, rather than being confined to a discrete subject. ● Curriculum Design: Curriculum frameworks can include fostering students' critical thinking, ethical understanding,

● Curriculum Design: Curriculum frameworks can include fostering students' critical thinking, ethical understanding, and practical skills in selecting, applying, and even crafting AI tools. This can be implemented with an awareness of the dynamic updates needed to remain relevant with rapidly advancing AI technologies.

Ethics, Safety, and Societal Impact

● Discussions of Bias and Fairness: AI systems can embed and exacerbate existing biases from their training data, leading to discriminatory digital divides. Classroom use must actively address these concerns, promoting critical evaluation of AI outputs for accuracy, bias, and misinformation. ● Authorship and Intellectual Property: AI's use of vast online data, often without consent, raises significant copyright

● Authorship and Intellectual Property: AI's use of vast online data, often without consent, raises significant copyright and intellectual property concerns. Students should learn about these issues, emphasizing responsible use, proper attribution, and acknowledging AI's contributions, while upholding academic integrity. ● Environmental Impact: Like the use of most technologies, there is an environmental cost of AI systems, which

● Environmental Impact: Like the use of most technologies, there is an environmental cost of AI systems, which require significant energy, materials, water, and contribute to carbon emissions. ● Well-being, Privacy, and Safety: Classrooms must ensure data privacy and user safety. This includes explicit

require significant energy, materials, water, and contribute to carbon emissions. ● Well-being, Privacy, and Safety: Classrooms must ensure data privacy and user safety. This includes explicit attention to children's rights and well-being, consideration of age limits for unsupervised AI interaction, and protection against manipulation or harmful content. Transparency and explainability are vital for users to understand how AI works and impacts them. ● Frameworks- Merits and Risks: Frameworks offer valuable perspectives on ethics, literacy, and responsible AI

works and impacts them. ● Frameworks- Merits and Risks: Frameworks offer valuable perspectives on ethics, literacy, and responsible AI use. At the same time, not all frameworks align with Montana’s cultural, legal, or rural context. These resources should be treated as adaptable references, rather than mandates, and they should be applied with local needs and values in mind.

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Creativity, Collaboration, and Critical Thinking

● Creative Expression: AI can serve as a powerful tool to expand creative expression, enabling new forms of text, art, and music. ● Collaborative Problem Solving: AI can support collaborative problem-solving by acting as a "thinking partner" to

● Collaborative Problem Solving: AI can support collaborative problem-solving by acting as a "thinking partner" to brainstorm ideas, refine outputs, or even simulate roles like a debate partner or research assistant. ● Critical Thinking and Judgement: Crucially, AI should prompt deeper critical thinking, not diminish it. Learners must

● Critical Thinking and Judgement: Crucially, AI should prompt deeper critical thinking, not diminish it. Learners must learn to evaluate AI-generated content for accuracy, relevance, and fairness, cross-referencing with reliable sources and questioning its outputs. This means nurturing human judgment and avoiding over-reliance or passive acceptance.

Family & Community Engagement

● Public Awareness and Shared Responsibility: Promoting AI literacy requires a multi-stakeholder approach, involving governments, intergovernmental organizations, civil society, academia, parents, and the private sector. ● Informing Families and Communities: Districts are encouraged to provide clear, accessible information (e.g.,

● Informing Families and Communities: Districts are encouraged to provide clear, accessible information (e.g., guides, workshops) to families and the wider community. This information should help families and communities to understand AI's implications, address misconceptions, and engage in informed decisions about its use, especially concerning children's rights, privacy, and well-being. Students, particularly children and youth, should be meaningfully engaged in conversations and decision-making about AI's impact on their lives.

Innovation

● Fostering Responsible Innovation: While AI offers immense potential for innovation and new forms of learning, it must be introduced with careful consideration and critical evaluation. The focus should be on evidence-based use cases that align with educational priorities, rather than simply novelty or hype. ● Tied to Instructional Goals and Monitored for Impact: AI applications should be validated for their ethical and

● Tied to Instructional Goals and Monitored for Impact: AI applications should be validated for their ethical and pedagogical appropriateness before large-scale adoption, ensuring they do no predictable harm, are effective for target learners, and align with sound pedagogical principles. Continuous monitoring and evaluation of AI systems are necessary throughout their life cycle to ensure robustness, integrity, and adherence to ethical guidelines, requiring re-certification if needed.

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# Professional Learning for Educators

Professional learning is essential to ensure that educators across Montana can use AI responsibly, effectively, and with confidence. This includes both technical skill development and the broader professional capacities needed to sustain human-centered education in the age of AI. Districts are encouraged to consult MTSBA’s model policies as they operationalize these principles within board-approved frameworks.

## Guiding Principles

- **Build Foundational AI Literacy: Educators at all levels should develop an understanding of what AI is, how it** works, its limitations, and its ethical implications. - **Embed Ethics and Equity: Training must emphasize bias awareness, fairness, data privacy, and the** importance of ensuring AI does not widen student access gaps. - **Support Role-Specific Skills: Professional learning should be scaffolded for different roles (teachers,** administrators, support staff), ensuring each group understands how AI intersects with and/or can support their responsibilities. - **Emphasize Human Oversight: Educators must learn to critically evaluate AI outputs, maintaining accountability** and ensuring that technology supports—not supplants—human judgment. - **Encourage Continuous Growth: Because AI tools evolve rapidly, professional learning should be ongoing,** flexible, and embedded within a culture of continuous improvement.

## Recommended Practices

- **Tiered Training: Provide introductory sessions for all educators, advanced workshops for instructional leaders,** and specialized sessions for technical staff and policymakers. - **Hands-On Practice: Create opportunities for educators to test AI tools in safe, low-stakes settings, allowing for** reflection on the benefits, risks, and instructional applications. - **Collaborative Learning: Encourage professional learning communities (PLCs) and cross-district networks to** share strategies, resources, and case studies of AI in practice. - **Family and Community Engagement: Offer parallel learning opportunities for families and communities so** they can understand how AI is used in schools.

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# Accessibility

Montana’s unique educational landscape, comprising rural, urban, and tribal communities, necessitates that AI integration be approached with a lens towards equal access. The goal is to ensure that all students, regardless of geography, socioeconomic background, language, or ability, benefit from safe and effective use of AI.

## Guiding Principles

- **Close Opportunity Gaps: AI should be deployed to expand—not limit—educational opportunity, ensuring that** underserved and under-resourced students are supported. - **Accessibility by Design: AI tools must meet accessibility standards (e.g., WCAG, Section 508) and provide** features such as text-to-speech, translation, and adaptive interfaces to serve students with disabilities and English language learners. - **Cultural Relevance and Respect: While AI may support instruction, fulfilling IEFA requires educator expertise** to ensure teaching strategies and content remain culturally relevant and respectful.

## Recommended Practices

- Prioritize funding and support for districts and schools that express interest in AI tools, particularly those serving high percentages of rural, tribal, or low-income students. - Districts and educators should honor tribes’ existing guidance and established approaches to delivering tribal content when considering the use of AI tools in education.

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# Data Privacy and Security

Protecting student information and upholding trust are foundational to the use of AI in Montana’s schools. This includes compliance with existing laws, strong local governance, and clear accountability.

## Guiding Principles

- **Legal Compliance: Comply with FERPA, COPPA, and Montana state laws regarding student data privacy.** - **Tool Purpose & Privacy: AI tools vary in purpose and data practices. General-purpose language models (such** as large-scale AI systems available to the public) differ from K-12 educational platforms designed specifically for school use under contract. Districts should apply the same standard of care—protecting student information, verifying vendor data practices, and avoiding the use of personally identifiable information—regardless of the tool type. - **Data Minimization: Collect only the data necessary for educational purposes and avoid unnecessary or** intrusive data collection. - **Indigenous Data Sovereignty: Respect tribes’ established guidance for delivering tribally authored materials** and managing tribal data. Use IEFA-aligned resources as provided, without altering or remixing them with AI tools. - **Security Standards: Maintain rigorous security practices, including encryption, access controls, and regular** audits.

## Recommended Practices

- Require contracts with vendors to include clear provisions for data protection, prohibiting secondary uses of student data such as advertising or model training. - Establish state-level vetting or procurement guidance to support districts in selecting AI tools that meet privacy and security standards. - Provide training for educators and administrators on responsible data practices, including how to evaluate vendor claims and ensure compliance. - Regularly review AI systems to confirm that data retention policies are followed and that information is deleted when no longer necessary. - Encourage districts to communicate privacy policies in accessible, family-friendly language, including translations where needed.

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# Policy and Governance

Policy and governance for AI in education in Montana must align with the state’s legal framework, cultural commitments, and practical realities of largely rural school systems. Districts must ensure that any AI-related policy or practice is grounded in Montana law and responsive to local needs.

## Constitutional Players

Montana’s “Constitutional Players” framework for governance of education distributes education authority across multiple entities, each with distinct roles in AI policy and implementation. These constitutional players include the Legislature, the Governor, the Board of Public Education, the Board of Regents of Higher Education, the Superintendent of Public Instruction, and local school boards. The Legislature sets statutory frameworks and funding parameters that shape AI adoption, while the Governor’s office coordinates cross-agency AI initiatives and workforce alignment. The Board of Public Education establishes administrative rules, educator preparation standards, and accreditation requirements that may include AI-related expectations, while the Board of Regents oversees higher education policy and research that inform the integration of AI within Montana’s colleges and universities. The Superintendent of Public Instruction provides guidance and technical assistance to districts on AI implementation, while local school boards make direct decisions about AI tool adoption, staff training, and student use policies within their communities.

The Montana School Boards Association (MTSBA) provides complementary guidance for local policy development and district-level implementation of AI. For the latest guidance from MTSBA, go to [http://mtda.link/mtsbaaipolicy](http://mtda.link/mtsbaaipolicy).

## Tribal Sovereignty and Consultation

Montana recognizes tribal governments across Big Sky Country, each possessing inherent sovereignty that predates the United States. Specific to educational curricula, the Montana Constitution stipulates that "The state recognizes the distinct and unique cultural heritage of the American Indians and is committed in its educational goals to the preservation of their cultural integrity."

Montana's constitutional commitment to inclusion of culturally respectful education about Montana's first peoples is reflected in the Indian Education for All Act, which requires all students to learn about the distinct heritage of American Indians. This law acknowledges the importance of teaching all students about Montana's tribal communities and cultures.

For AI use, tribal sovereignty means that tribes maintain jurisdiction over their data and digital materials, have the inherent right and authority to regulate the deployment of technology that affects their communities, and the right to determine whether and how AI systems interact with their cultural knowledge. Those drafting AI policies must recognize tribal authority over these technologies and ensure that any resulting policies are the result of meaningful consultation when state AI initiatives could impact tribal communities or infringe upon their data sovereignty rights.

## Local Control and Rural Realities

Montana's commitment to local control means that AI decisions ultimately rest with individual school districts, but rural realities create unique implementation challenges. Small districts may lack dedicated technology staff, may have limited broadband infrastructure, and constrained budgets that affect AI tool selection and support. Rural schools may need to rely on regional cooperatives, state-provided resources, or shared services agreements to effectively evaluate and implement AI solutions. Additionally, Montana's geographic isolation means that many districts require AI tools that function reliably with intermittent connectivity and can be managed remotely. Local boards must balance the promise of AI-enhanced learning with practical constraints of rural implementation, ensuring that any AI adoption aligns with community values and actually improves educational outcomes rather than creating additional administrative burden for already stretched staff.

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# Governance Practices for Districts

## District-level AI governance should include:

- Adoption of local AI policies tied explicitly to MCA and ARM references. - A data privacy review process and model contract language consistent with Montana law. - Rural-scaled implementation options that account for local capacity and shared services.

# Higher Education/Workforce Connections

Montana's AI education policies must align with the state's higher education institutions and workforce development priorities to create coherent pathways for students. The Montana University System plays a critical role in preparing teachers who can effectively integrate AI tools and in conducting research that informs K-12 AI implementation.

# Student and User Data Privacy

Montana schools are regulated by a robust set of expectations regarding student and user data privacy.

Federally, schools must follow FERPA (Family Educational Rights and Privacy Act), which sets baseline privacy protections for student education records, and must ensure compliance with COPPA (Children's Online Privacy Protection Act), which allows schools to consent on parents' behalf for educational technology use but requires that vendors meet COPPA requirements when collecting personal information from children under 13.

At the state level, Montana schools must comply with the Montana Pupil Online Personal Information Protection Act, which includes two key statutes: 20-7-1325 (Online Protections for Pupils) prohibits educational technology companies from engaging in targeted advertising, selling student information, or using protected data for non-educational purposes, while 20-7-1326 (Pupil Records -- Online Privacy Protections) requires school districts to include specific privacy safeguards in contracts with third-party vendors who provide digital educational services or cloud-based storage of student records.

Schools should work with vendors that provide detailed, written information regarding their specific compliance with these laws and expectations. When applicable, schools require vendors to provide a Montana Student Data Privacy Agreement.

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# Implementation Roadmap

Successful AI integration requires careful planning, regional collaboration, and support from trusted external partners. Montana’s size, rural context, and diversity of district composition make it essential to provide flexible, scaffolded pathways for implementation.

## Capacity Building Supports

- **Montana Digital Academy (MTDA): MTDA, via the Frontier Learning Lab, can provide professional learning to** help districts pilot and scale AI-supported practices and vetted platforms. - **Regional Service Agencies and Cooperatives: These agencies can deliver training, host professional learning** communities, and provide shared technical expertise for small or remote districts that cannot sustain standalone initiatives. - **State Education Organizations: The Montana School Board Association, School Administrators of Montana,** Montana Rural Education Association, Map of Montana Small School Alliance, and regional education cooperatives can provide guidance and professional learning. - **Higher Education Partnerships: Universities and community colleges—including Montana’s tribal** colleges—may offer opportunities for joint training, research, and educator preparation aligned with AI literacy and implementation goals.

### I. Establishing a Strong Foundation and Vision

The first phase lays the groundwork by defining a clear vision and engaging stakeholders.

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- **Define Purpose and Goals: Articulate why AI matters, linking efforts to district priorities and educational vision.** The goal is to enhance student outcomes and empower educators, rather than adopting technology for its own sake. - **Convene a Diverse Team: Form a cross-functional committee of administrators, teachers, IT leaders, students,** parents, tribal leaders, and community members to guide AI use and ensure local needs are addressed across rural, urban, and tribal settings. - **Introductory Training: Provide orientation for district leaders, board members, and student leaders to build a** shared understanding of AI’s potential, limits, and ethical considerations.

## II. Developing Policies and Practices for Responsible Use

This stage ensures AI integration is safe, ethical, and equitable.

- **Review and Update Policies: Adapt existing policies on academic integrity, acceptable use, privacy, grading,** and digital citizenship to include AI. - **Establish Core Principles: Ground all policies in shared values: privacy, transparency, accountability,** accessibility, human oversight, and academic integrity. - **Promote Transparency and Communication: Share clear information about AI’s benefits, risks, and** safeguards, and invite community feedback. - **Vendor Vetting: Require clear contracts with AI providers that address data security, privacy, and bias** mitigation. Avoid entering personally identifiable information (PII) into unauthorized tools. - **Emphasize Human Oversight: Ensure AI supplements—not replaces—educator judgment. All AI-generated** content should be critically reviewed before classroom use.

## III. Capacity Building and Professional Learning

Sustained development for staff is essential for meaningful use.

- **Differentiated PD: Provide role-specific professional learning on AI literacy, ethics, privacy, and practical** strategies. - **Hands-On Practice: Create safe spaces for educators to test tools, reflect on risks and benefits, and** collaborate in PLCs or cross-district networks. - **AI Literacy for All: Ensure all staff and students develop a baseline understanding of what AI is, how it works,** its limitations, and how to use it responsibly.

## IV. Accessibility and Implementation Pathways

AI adoption must benefit all students, regardless of their geographic location or circumstances.

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- **Close Digital Gaps: Provide access to devices, connectivity, tools, and platforms with special attention to rural,** underserved, and tribal communities. - **Pilot, Then Scale: Start with small pilots to refine approaches before broad adoption.** - **Rural-Scaled Options: Leverage cooperative and shared contract options for small schools with multi-role** educators and mixed-age classrooms. - **Higher Education & Industry Partnerships: Partner with universities, tribal colleges, industry, and workforce** programs to develop relevant and culturally responsive applications. - **Inclusive Design: Prioritize tools that meet accessibility standards and serve students with disabilities and** multilingual learners.

## V. Monitoring, Evaluation, and Continuous Improvement

Because AI evolves quickly, integration requires ongoing reflection and adjustment.

- **Regular Reviews: Update policies and practices semi-annually or annually to keep pace with technological and** legal shifts. - **Feedback Loops: Collect input from students, staff, and communities to improve over time.** - **Track Impact: Measure whether the use of AI improves equity, instruction, well-being, and data security.** - **Share Best Practices: Disseminate lessons learned and success stories statewide to accelerate collective** growth. The Frontier Learning Lab, a program of MTDA, provides statewide support for this roadmap, offering expertise, professional learning, model policies, and collaborative networks to help Montana schools implement AI responsibly and effectively. The Frontier Learning Lab can be contacted through [ai.help@montanadigitalacademy.org](mailto:ai.help@montanadigitalacademy.org)

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# Glossary

The glossary provides shared language for Montana educators, families, and policymakers as they engage with AI in education. Terms are drawn and adapted from national frameworks.

## Artificial Intelligence (AI): Computer systems designed to perform tasks that typically require human intelligence, such

as recognizing speech, analyzing data, making predictions, or generating text and images.

**Generative AI: A type of AI model trained on large datasets that can create new content—such as text, images, audio,** or code—based on patterns in its training data.

**Large Language Model (LLM): A type of artificial intelligence trained on vast amounts of text data that can generate** human-like responses, complete tasks such as writing or summarizing, and answer questions. LLMs, such as ChatGPT or Gemini, rely on patterns in language rather than true understanding, which means their outputs require human review and oversight.

**Algorithm: A step-by-step set of rules or instructions that a computer follows to perform a task or solve a problem.**

**Bias (in AI): Systematic and unfair outcomes that result when AI models reflect prejudices or imbalances present in** training data or design.

**Data Privacy: The right of students and families to control how personal and educational information is collected,** stored, used, and shared.

## Digital Literacy: The knowledge and skills required to use digital technologies effectively, responsibly, and safely,

including evaluating online content and understanding data practices.

**AI Literacy: The knowledge, skills, and habits of mind that support the safe, effective, and ethical use of artificial** intelligence, fostering informed decision-making and critical engagement with AI tools and their outputs.

**Academic Integrity: A commitment to honesty and responsibility in scholarship and learning, requiring students to use** AI tools in ways that support—not replace—original thinking and reflection.

**Human Oversight: The active role of educators and administrators in reviewing, interpreting, and guiding AI use to** ensure that technology enhances, rather than replaces, human judgment.

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# References

This section provides a working list of references used to inform the Montana AI in Education Guidelines. Sources include state guidance from peer states, national frameworks, and Montana-specific statutory and constitutional anchors.

## State Guidance Documents

- Massachusetts Department of Elementary and Secondary Education. Guidance for Artificial Intelligence in K–12 _Education. Massachusetts DESE, 2024._ - Utah State Board of Education. Artificial Intelligence in Education Guidance. Utah State Board of Education,

- Wyoming Department of Education. Artificial Intelligence Guidance for Schools. Wyoming Department of Education, 2024. - Colorado Department of Education. AI Guidance for Educators. Colorado Department of Education, 2024. - North Carolina Department of Public Instruction. Generative AI Implementation Recommendations and _Considerations for PK–13 Public Schools. NCDPI, 2024._ - Montana School Boards Association. Model Policies for Artificial Intelligence Integration in Education. MTSBA,

## National and International Resources

- International Society for Technology in Education (ISTE). ISTE Standards for Students and Educators. ISTE,

2023. [https://www.iste.org/standards](https://www.iste.org/standards)

- Computer Science Teachers Association (CSTA). K–12 Computer Science Standards. CSTA, 2023. [https://csteachers.org/ka2standards/](https://csteachers.org/ka2standards/) - Organization for Economic Co-operation and Development (OECD). Empowering Learners for the Age of AI: An \*AI Literacy Framework for Primary and Secondary Education. OECD, 2025. [https://ailiteracyframework.org\*](https://ailiteracyframework.org*/) - National Center on Education and the Economy (NCEE). AI in Education Initiatives. NCEE, 2025. [https://ncee.org](https://ncee.org/)

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# Montana Constitutional and Statutory Anchors

- Montana Office of Public Instruction. Indian Education for All – Essential Understandings Regarding Montana \*Indians. OPI, [https://opi.mt.gov/Educators/Teaching-Learning/Indian-Education-for-All\*](https://opi.mt.gov/Educators/Teaching-Learning/Indian-Education-for-All*) - Montana Secretary of State. Administrative Rules of Montana (ARM) 10.55 – Accreditation Standards. State of Montana, [https://rules.mt.gov/gateway/RuleNo.asp?RN=a0.55](https://rules.mt.gov/gateway/RuleNo.asp?RN=a0.55) - Montana Secretary of State. Administrative Rules of Montana (ARM) 10.57 – Educator Licensure. State of Montana, [https://rules.mt.gov/gateway/RuleNo.asp?RN=10.57](https://rules.mt.gov/gateway/RuleNo.asp?RN=10.57) - Montana Legislature. Montana Code Annotated, Title 20 – Education Statutes. State of Montana, 2024. [https://leg.mt.gov/bills/mca/title\_0200.htm](https://leg.mt.gov/bills/mca/title_0200.htm) - Montana Legislature. Montana Student Online Personal Information Protection Act. State of Montana, 2019. [https://leg.mt.gov/bills/mca/title\_0200/chapter\_0100/part\_0150/section\_0010/0200-0100-0150-0010.html](https://leg.mt.gov/bills/mca/title_0200/chapter_0100/part_0150/section_0010/0200-0100-0150-0010.html)

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# How AI Supported the Development of this Document

This document was developed through a collaborative process led by the Montana Office of Public Instruction (OPI), MTDA’s Frontier Learning Lab, and partner educators. Artificial Intelligence (AI) tools were used in limited but intentional ways to assist with research, drafting, and synthesis. Human authors retained oversight, reviewed all AI contributions, and made all final editorial and policy decisions.

## Specific uses of AI included:

- **Comparative Research: AI was used to review and summarize policy guidance from peer states (e.g.,** Massachusetts, Utah, Colorado, North Carolina, Wyoming) as well as national and international frameworks (e.g., ISTE, CSTA, OECD). - **Draft Support: AI provided suggested language for principles, implementation pathways, and glossary** definitions, which were then revised and validated by Montana educators and policymakers. - **Document Design: AI tools assisted in generating illustrative graphics (e.g., front-page cover art) aligned with** Montana’s cultural and educational context.

## Commitment to Human Oversight

Consistent with the principles provided in this document, AI was not used to make policy determinations or high-stakes judgments. All AI outputs were critically reviewed, edited, or replaced by human authors. This approach demonstrates responsible AI use in practice; leveraging efficiency and comparative research strengths of AI while ensuring Montana’s values, priorities, and legal frameworks remain at the center.