In Byram Hills, we aim to “... provide students with the means, knowledge, and opportunity to excel in order to become productive and responsible citizens and leaders of the twenty-first century” (the Byram Hills Mission Statement). To address the mission, we equip students with the knowledge and tools to effectively harness artificial intelligence (AI) and large language models (LLMs) in ways that enhance and transform their educational experience. We are committed to providing meaningful and safe opportunities to engage with emerging technologies that foster the durable skills of critical thinking, communication, creativity, and collaborative problem-solving. Through professional learning and intentional strategies, educators will guide students in leveraging AI ethically and responsibly. 

Not only must students learn to use AI to enhance their learning, but learning about AI will increase students’ job marketability in many fields of study, both in and out of the technology industry. The World Economic Forum’s Future Jobs Report (2023) noted that more than 75% of companies will adopt AI technology within the next five years. Students must understand such topics as data science, robotics, machine learning, and prompt engineering, which will amplify job perspectives in fields such as biotechnology, pharmaceuticals, and engineering. The future job market will require individuals who are flexible, adaptable, and critical thinkers.  

To meet our vision of growing durable skills and AI knowledge for future job perspectives, this document provides guidance on the use of AI to enhance learning experiences and outcomes, ensure appropriate use, maintain high ethical standards, and uphold our commitment to data privacy and security.

Ethical use of artificial intelligence is critical to realizing the full potential of generative AI in education and preparing students for the world beyond high school. This demands a clear understanding of the technology, coupled with proactive attention to specific ethical issues, such as:

• Privacy: AI tools often collect and process student data, raising concerns about their security, access, and potential misuse. 
• Academic Integrity: The ease with which AI can generate content raises concerns about plagiarism and the devaluation of original work. 
• Bias: AI algorithms can perpetuate and amplify existing biases, possibly leading to unfair or discriminatory information for certain groups.
• Equity: Unequal access to AI tools and the technology required to use them can exacerbate existing disparities between students.
• Transparency and Explainability: The "black box" nature of some AI systems can make it difficult to understand how they arrive at decisions, hindering accountability and trust.

We must continuously reflect on the use of AI, discuss its effect on these ethical issues, and adapt as we learn about AI's evolving impact on learning. By prioritizing these ethical considerations, we can harness AI to enhance education, guided by enduring principles of academic integrity, privacy and security, critical evaluation, and accountability

These guiding principles are discussed in the following sections to build common knowledge and provide guidance to ensure ethical use of AI tools.

We define the following terms and concepts in order to facilitate a common understanding of artificial intelligence as we navigate this complex new technology. 

Technology Terms

• Artificial Intelligence (AI): The simulation of human intelligence processes, including learning, reasoning, and self-correction.
• Generative Artificial Intelligence (GenAI): A type of AI that learns patterns and structures from vast amounts of data (text, images, audio, etc.) to generate new content. 
• Algorithm: A set of rules or instructions that a computer follows to solve a problem or complete a task.
• Large Language Models (LLMs): An AI model trained on a massive amount of text data, enabling it to understand and generate human-like text. LLMs are used for various tasks, including text summarization, translation, and question answering.
• Generative Pre-trained Transformer (GPT): A specific type of LLM architecture developed by OpenAI. GPT models are known for their ability to generate coherent and contextually relevant text.
• Training Data: The data used to teach a machine learning model to recognize patterns and make predictions.
• Hallucination in AI and LLMs: Systematic errors result in inaccurate, false, or fabricated outputs due to flawed training data or algorithms, but are presented as factual.
• Prompt: The basic unit of text that an LLM processes. 
• Adaptive Learning: An educational approach that uses AI to adjust the difficulty and pace of instruction based on a student's performance.
• Chatbots: AI-powered experiences that can answer questions and offer personalized feedback. Chatbots simulate conversations. 

Data Privacy Terms

• Ed-Law 2D: New York State education law prohibits the unauthorized release of personally identifiable information and establishes data security and privacy standards for educational agencies and third-party contractors. 
• FERPA: The Family Educational Rights and Privacy Act is a U.S. federal law that protects the privacy of student education records. 
• CIPA: The Children’s Internet Protection Act is a federal law that requires schools to use filtering software to protect students from harmful or inappropriate content. 
• COPPA: The Children’s Online Privacy Protection Act is a federal law that regulates how websites collect personal information from children under 13 years of age. 
• Third-Party Data Sharing: The practice of sharing student data with external vendors or service providers.

Academic Integrity Terms

• Ethical Use of AI: Using AI tools in a responsible manner that upholds academic integrity and promotes genuine learning.
• Citation in AI:  A reference to the original source of information, ideas, or images used in one’s work

The District is committed to protecting student data privacy and ensuring the safety of all users. To that end, the District will:

• Evaluate AI tools for compliance with all relevant policies and regulations;
• Adhere to all applicable federal, state, and local laws, including FERPA, CIPA, and COPPA;
• Enforce the Technology and Network Acceptable Use and Personal Privacy;
• Prohibit staff and students from entering confidential or personally identifiable information into unauthorized AI tools; and 
• Review all AI tools to ensure they are developmentally appropriate and do not pose a risk to students.

The District uses a rigorous process to evaluate that software platforms comply with NYS Education Law 2D and serve an educational purpose. Any questions regarding privacy and security practices can be directed to the director of technology. 

Critical evaluation, as it relates to AI bias and fairness, involves a systematic and rigorous assessment of AI systems to identify, understand, and mitigate potential biases and misinformation. It goes beyond simply checking if an AI system is accurate; it delves into how the system arrives at its conclusions and whether those conclusions are accurate and appropriate. In Byram Hills, we provide our educators and students with the skills and knowledge to critically evaluate AI systems, identify bias and inaccurate information, and understand the impact AI has on information dissemination. 

Here are some key aspects of critical evaluation in this context:

• Identifying Sources of Bias: Examining the data used to train the AI algorithms and the design choices made during development.
• Assessing Impact: Analyzing the potential consequences of biased AI systems on individuals and groups.
• Auditing AI Systems: Conducting thorough evaluations of AI systems to ensure they comply with ethical guidelines and legal standards.
• Promoting Transparency and Explainability: Advocating for AI systems that are transparent in their decision-making processes, allowing for scrutiny and accountability.

Specifically, we train educators and students to: 

• Identify bias and fairness in AI systems. 
• Explain the importance of critical evaluation as consumers of information and learning.
• Utilize best practices when engaging with AI systems. 
• Use human judgment when using and evaluating the output of AI.
• Cite the use of AI where appropriate and required.

Learning is at the heart of education. The Byram Hills mission seeks to “... provide students with the means, knowledge, and opportunity to excel in order to become productive and responsible citizens and leaders of the twenty-first century.” While artificial intelligence and other technologies can assist students with learning, true knowledge comes from one’s own effort. Learning is not just finding information; it’s about understanding at a deeper level, applying and making connections, and explaining ideas and concepts. 

No technology can replace a student’s hard work in mastering new skills and understanding. Nonetheless, technological advancements like AI can be a powerful learning partner when used thoughtfully. This toolkit will guide students in using AI responsibly, show them how it can enhance their learning, and foster open communication between students, teachers, and families as we navigate this evolving technology together.

Students need not worry! A few reminders to students will ensure we maintain an open dialogue about the appropriate use of AI and prepare students for future learning endeavors:

• If you are unsure if you can use AI, ask! Your teachers will provide clear guidelines for each assignment.
• Review the output from AI carefully. Remember that AI can “hallucinate” or produce inaccurate information. Always corroborate the information with other reliable sources.
• If you receive inappropriate content from AI, speak with a trusted adult immediately. 
• Do not sign up for AI tools if you are unclear about the data being collected. Never input any personal information about yourself or others into an AI tool. Ask your parents for guidance.
• Review the Code of Conduct and any guidance documents shared by our teacher. Remember that there are consequences for violating the academic integrity rules.

The capacity of AI tools to generate various content (text, audio, video, artwork, etc.) and solve problems raises significant concerns about academic integrity, particularly the challenge of distinguishing between original work and AI-generated content. The District reaffirms its commitment to academic integrity, ensuring that technology serves to enhance, not hinder, student learning.

To uphold our high academic standards, the District will enforce the Code of Conduct (Board of Education Policy 5300), the Technology and Network Acceptable Use and Personal Privacy (Board of Education Policy 4526), and Student Use of Internet-Enabled Devices (Board of Education Policy 5695.) All members of the Byram Hills community are responsible for understanding and adhering to these policies. Appropriate consequences for the inappropriate use of artificial intelligence will be applied in the same way as in any case of academic integrity violations. Questions regarding academic integrity and related policies should be directed to faculty, building principals, and District administrators.

This document will provide guidance on what constitutes academic integrity, including the appropriate citation of AI use, specific expectations for each academic department, and examples of how educators can use AI in the classroom. Ultimately, we are all accountable for fostering a strong culture of academic integrity.

Original work must demonstrate the highest standards of authenticity, with proper acknowledgment of all sources. AI-generated content must be cited using common style formats such as APA or MLA.

To maintain academic integrity and prevent misunderstandings, students must consult with their teachers before using AI tools for assignments. Students are responsible for understanding their teachers' expectations for AI use, both generally and for specific assignments.

Teachers will communicate their specific rules and expectations regarding AI use to students at the beginning of the year and in relation to individual assignments. Clear and ongoing communication among educators, students, and families is essential to fostering a shared understanding of academic integrity. Students must clarify any uncertainties regarding expectations, as these may vary by teacher and assignment.

Below are examples of citations using various styles and content areas. Students should inquire about their teachers’ preferred citation methods.  

Example 1: Citing AI-Generated Text (APA Style). Using ChatGPT to brainstorm ideas for a persuasive essay in English class. Citation Example: 

ChatGPT. (2024, Jan 25). List of potential persuasive essay topics. OpenAI. www.chat.openai.com

Example 2: Citing AI-Generated Code (MLA Style). Using CoPilot to generate a Python function for a math assignment. Citation Example: 

“Calculate_average.” GitHub Copilot, Version 1.139.0, GitHub, 2024. https://github.com/features/copilot.

Example 3: Citing AI-Generated Image (Chicago Style). Using DALL-E 2 to create an image for a history project. Citation Example: 

DALL-E 2, Painting of a historical figure. OpenAI, 2024. https://openai.com/dall-e-2/.

Example 4: Citing AI Assistance in Data Analysis (Harvard Style). Using an AI tool to help analyze data for a science experiment. Citation Example: 

Tableau (2024) Assisted in identifying key trends. Salesforce. Available at: https://www.tableau.com/ (Accessed: 2024-02-15).

Example 5: Citing AI-Generated Summary (MLA Style). Using an AI tool to summarize a long article for an English class. Citation Example: 

SummarizeBot. "Summary of 'The Fall of the House of Usher.'" Awesome Summarization, 2024, https://awesomesummarization.com/summarizer.

Google. (2025, March 29). Output from Gemini (Flash 2.0). Retrieved from gemini.google.com.  

Artificial intelligence offers unprecedented opportunities to personalize and enhance student learning experiences. By using AI tools responsibly, students can develop a deeper understanding of content, improve their critical thinking and problem-solving skills, and practice creative expression. 

Here are some ways AI can support student learning:

Assisting with Learning:

AI tools can enhance the student learning experience by creating customized study guides, quizzes, and visual representations. Examples include:

• Create a study guide for a history exam, focusing on specific eras where a student consistently struggles, with targeted practice questions and summaries.
• Create flashcards for vocabulary memorization that adjust to the student's learning pace and repeat words that are frequently missed.
• Create a graphic organizer for events in a text to assist with writing a paper on a topic related to the text. 

Acting as a Personalized Tutor:

AI tools can provide instant feedback on student responses, offering explanations and alternative approaches. Examples include: 

• An AI tutor poses progressively challenging problems in math, giving step-by-step guidance and correcting errors in real-time.
• An AI language tutor engages students in simulated conversations, providing feedback on pronunciation, grammar, and vocabulary.
• Provides questions on a science topic and prompts students to expand their thinking and make connections across disciplines. 

Aiding in Creativity and Innovation:

AI tools can inspire creative expression by generating ideas, providing prompts, and facilitating multimedia creation. Examples include: 

• Use an AI image generator to create visual representations of scenes from a novel, enhancing their understanding of literary imagery. 
• An AI music generator creates a soundtrack for a paper that enhances the text.

Developing Critical Thinking and Problem-Solving Skills:

AI can present students with complex scenarios, simulations, and data analysis tasks that require critical thinking and problem-solving. Examples include: 

• Use an AI-powered simulation to analyze environmental data and propose solutions to a hypothetical ecological crisis.
• Generate diverse viewpoints on a current event, prompting students to evaluate sources, identify biases, and form their own informed opinions.

Google. (2025, April 6). Output from Gemini (Flash 2.0). Retrieved from gemini.google.com.  

While there are many exciting and appropriate learning opportunities with AI tools, students must know and understand each classroom teacher’s expectations for AI use in the course and on specific assignments. Students must also be familiar with the Code of Conduct and AUP (refer to the academic integrity section of this document) and know that appropriate consequences will follow for any violations of academic integrity. 

In the end, AI tools cannot replace the time students spend reading, reviewing and recalling new content, practicing new skills, and applying new learning to new situations. 

Secondary Level (Grades 6-12)

The appropriate use of artificial intelligence tools may vary across academic disciplines, courses, and specific assignments based on the required and relevant learning demands. As a result, each academic department in grades 6-12 provides guidance on the appropriate use of artificial intelligence tools. Classroom teachers will share the guidance at the start of each school year and remind students of appropriate use throughout the year. It is the student’s responsibility to be certain to understand the expectations for AI use in the classroom and on specific assignments. 

Below are the current guidance documents created by the faculty and department director or chairperson for students in grades 6-12. These documents will be revised and updated periodically as we continue to evaluate the impact of AI on student learning. 

The guidance from each department highlights appropriate use of AI, use of AI with permission, and areas in which AI use is not allowed. Reach out to department chairpersons and directors if you have questions regarding specific guidance documents.  

Elementary Level (Grades K-5)

While students in grades 6-12 may directly use artificial intelligence tools, elementary-age students are less likely to use AI themselves. Nonetheless, teachers may use AI tools to create appropriate activities, assessments, readings, or student demonstrations in a variety of ways. 

Below are examples of ways AI may be used in the elementary grades.

It's important to note that age restrictions for AI and GPT tools are in place primarily to protect children's privacy and ensure compliance with legal regulations. Key considerations include: 

COPPA (Children's Online Privacy Protection Act)

This U.S. federal law protects the online privacy of children under 13, requiring parental consent for the collection of their personal information.

GDPR (General Data Protection Regulation)

This European Union law sets rules for data protection, including those related to children. It can influence how companies operating globally handle user data.

Terms of Service

AI and GPT platform providers set their own terms of service, which often include age restrictions. These restrictions are intended to protect both the company and the user.

Specific Tool Considerations

• Many popular AI tools and platforms require users to be at least 13 years old.
• For users under 18, parental or guardian consent may be required.
• Specific Examples:

ChatGPT: Individual personal ChatGPT accounts are available for users aged 13 and older with parent or legal guardian permission.

Google Gemini: Google Gemini has age restrictions and requires users to be 13 years of age.

Microsoft Copilot: Microsoft enforces age restrictions for Copilot through the use of Microsoft Accounts. If the user is under the age of 13, parental consent is required.

Byram Hills does not provide students access to ChatGPT, Google Gemini, or Microsoft Copilot. The District reviews all technology tools in accordance with state and federal laws and regulations. The District has licensed AI tools that have been vetted and are monitored by faculty and the Technology Department.   

The type of technology used is less important than the level of thinking required for student learning. As we engage students with AI and other technologies, the level of cognition is at the heart of the task design. Teachers regularly use various models when designing lessons based on specific curricular goals. This section provides several models for teachers to use in designing lessons with AI. 

First, teachers analyze the need for technology when designing lessons. The SAMR model is one tool that can help teachers evaluate the technology needs. 

Second, models such as Bloom’s Taxonomy and Webb’s Depth of Knowledge are often used to align tasks with the desired level of cognition. Examples of how AI can be used to engage students with explanations for Bloom and Webb are provided below. 

Third, various prompt frameworks are provided to assist in producing strong outputs from various AI tools. As with all media use, teachers use careful judgment in evaluating the quality of the work produced by AI. 

Finally, this section provides additional information, including District-approved AI tools, professional learning opportunities, and information about the role of the technology department. 

As innovative technologies emerge, the District uses a four-level technology integration framework, SAMR, developed by Dr. Ruben Puentedura. The SAMR framework highlights technology that either enhances the tasks (substitution and augmentation) or transforms the tasks (modification and redefinition.) The SAMR model is defined in the following way:

The SAMR model serves as a continuum based on the goals of a lesson. Consideration is given to the skills, knowledge, and understandings that are required at a particular time in the curriculum. Educators use this model as they integrate technology in the classroom. 

Below are examples of how AI can be used in each of the four levels of integration: 

1. Substitution: Instead of writing a traditional lecture summary on a whiteboard, the teacher uses AI to generate a concise summary of a complex historical event, which is then displayed on a projector.

2. Augmentation: The teacher uses AI to generate multiple versions of practice problems for a math lesson, varying difficulty and context, allowing for differentiated instruction.

3. Modification: The teacher uses AI to create a personalized interactive dialogue between historical figures, allowing students to explore different perspectives and motivations in a more engaging way.

4. Redefinition: The teacher uses AI to create a simulated world where students can interact with historical figures and events in real time, engaging in role-playing and problem-solving scenarios that were previously impossible.

 Google. (2025, March 26). Output from Gemini (Flash 2.0). Retrieved from gemini.google.com.  

Additionally, the School Library Systems of NY developed an  AI Scope and Sequence as a framework for the teaching of AI concepts, organized by grade bands. The document lays out four strands that connect computer science, media literacy, and information fluency. The strands include: 

Strand 1: Why AI: The Evolution and Integration of AI into the World and My Life 

Strand 2: How AI Works: Technical Aspects and Functionality of AI 

Strand 3: AI in Society: Ethics and Other Questions About AI

Strand 4: AI in Practice: Being a Productive and Responsible User  

The library media specialists are prepared to collaborate with educators to create curriculum connections and curate resources aligned to the concepts in this document.

Depth of Knowledge (DOK) is another type of framework used to identify the level of rigor for assessments or learning tasks. In 1997, Dr. Norman Webb developed the DoK to categorize activities according to the level of complexity in thinking that is required of a task or assessment item. Teachers design lessons, activities, and assignments aligned to the DOK levels. The four levels of Webb’s DOK framework are defined in the following chart:

Source: https://www.structural-learning.com/post/webbs-depth-of-knowledge

Below are some examples of how teachers might use AI tools aligned to the DOK levels:

Examples were originally generated by the following source and modified as appropriate:  

Google. (2025, April 6). Output from Gemini (Flash 2.0). Retrieved from gemini.google.com. 

Bloom's Taxonomy is a hierarchical framework for classifying learning objectives, developed by Benjamin Bloom and his colleagues, that outlines six levels of cognitive learning. Teachers design lessons, activities, and assignments aligned to the various levels as learning becomes more complex over time. The framework is defined by this common pyramid, followed by verbs to use when designing tasks:

Below are some examples of how teachers might use AI tools aligned to the levels of Bloom’s:

Examples were originally generated by the following source and modified as appropriate: 

Google. (2025, April 6). Output from Gemini (Flash 2.0). Retrieved from gemini.google.com.

The quality of output from AI lies in the detail of the prompt that is asked. Various frameworks exist that can guide educators in creating prompts to produce a quality response from the AI tool. One valuable prompt, from Fitzpatrick, Fox, and Weinstein, includes a first response framework, PREP, and then a framework for evaluating the quality of the prompt, EDIT. (See below.)  

Designed specifically for educators, AI for Education created the Five S framework for educators and one for students. These prompts give guidance on ways to use prompts for quality AI output. 
 

Lesson planning can take considerable time. The chart below highlights key lesson plan elements and ways to use AI to assist in creating tasks or instructional suggestions. As with any curriculum, educators use their knowledge, professional judgment, and grade-level standards when interpreting AI outputs. 

Additional prompts exist; educators and students are encouraged to explore them as they generate AI commands for various purposes. The following chart gives an array of prompts for exploration. 

The District carefully reviews all technology software to ensure compliance with state and federal law and with Board of Education policies. Students may only use approved District software platforms while in school and when using District devices. 

You can review the current list of approved software on the District website: 

https://www.byramhills.org/academics/academic-departments/technology/approved-apps-software 

The District continually reviews and evaluates new software to maintain innovative products for teacher and student use. 

The District has long relied on the tenets of systems thinking to foster continuous, lifelong learning in pursuit of its mission. The use of generative AI and other emerging technologies is no different. Donella Meadows, a renowned systems thinker, said :

“The Future can’t be predicted, but it can be envisioned and brought lovingly into being…We can’t control systems or figure them out, but we can dance with them.” (Dancing with Systems, 2001) 

Like Peter Senge’s vision of a learning organization that has long provided the structures that define Byram Hill’s approach to professional learning, Meadows highlights the importance of adaptability, collective vision, and continuous learning rather than rigid control. Both Meadows and Senge advocate for an approach that fosters creativity, responsiveness, and a holistic understanding of complex systems. The opportunities below highlight the ways in which we continuously improve our understanding of generative AI’s impact on teaching and learning.

Professional Learning Communities: 

Byram Hills uses the District’s Professional Learning Communities to discover and share uses of generative AI in order to benefit student learning. The professional learning community structure includes opportunities to discover emergent technologies, think together about the most appropriate use in the classroom, experiment with technology integration, and share practices that enhance student learning. Furthermore, the facilitators of Learning Communities are provided additional training and time to learn technology tools in order to lead grade-level or departmental teams.    

This structure provides the means for teachers to engage in three important components of professional learning: to discover new technology, to embed technology into instruction, and to reflect on the impact on student learning.  

Cyber Camp

Each summer, the District offers opportunities for teachers to learn together. Cyber Camp provides time for teachers across grades and departments to collaborate and learn new technologies. The building technology coordinators, in collaboration with with director of technology, design and facilitate Cyber Camp session to provide time for teachers to integrate new technologies into their lesson plans. 

Learning Lab

The Byram Hills Learning Lab (in-service courses) provides opportunities for teachers to engage deeply in coursework related to District initiatives.  Courses have been carefully developed with District partners to support learning and engagement with generative AI technologies.  

Faculty, Department, and Grade Level Meetings

Additional time to explore AI tools occurs during faculty meetings, grade-level meetings, and departmental meetings throughout the year. Teachers can discuss topics or new learning related to emerging AI issues and use the time to integrate AI into their lessons.  

The technology department studies emerging technologies and maintains current knowledge of state and federal legislation related to new technologies. The director of technology and the staff play a key role in remaining updated on technology platforms and policies that impact schools. 

Key areas of focus for the technology department related to artificial intelligence include: 

• Provide ongoing professional learning opportunities and resources for educators. 
• Evaluate all software used in the District in terms of compliance with state and federal laws and educational value.
• Manage data privacy and security. 
• Monitor the appropriate use of technology in the District. 

Visit the technology department webpage for detailed information. 

The District will regularly evaluate the impact of AI technology on student learning and update this guidance document as appropriate. Furthermore, information gleaned from the evaluation will be used to update the ways in which we instruct students, communicate expectations, and provide resources. 

The following outline will guide our evaluation process: 

1. Timeline: Collect and analyze feedback at least once per year. 
2. Participants: Feedback will be solicited from students, educators, and families. Additional feedback will be collected from various community-based organizations and expert consultants. 
3. Data Collection: 
   1. Surveys will provide information on student and educator use of AI, including benefits and challenges, and from families on their observations of their children’s use of AI tools.
   2. Interviews and focus groups allow for a more in-depth understanding of how one thinks about AI use and the guidance provided by teachers and the District. 
   3. Data usage reports can provide insight into what tools are used regularly and how they are being used. 
   4. Student work samples using AI will be analyzed against benchmarks for critical thinking, creativity, collaboration, and communication, and for depth of thinking (using Bloom’s Taxonomy and Webb’s Depth of Knowledge.) 
   5. Professional learning evaluations will provide insight into the training provided by the District.
4. Analysis: Information from the various data collection methods will be conducted by a group of educators and shared with relevant stakeholders. Recommendations will be made to update this guidance document and to other relevant aspects of the District program and school functions, which may include such areas as training programs, instructional strategies, and communication of expectations.

Below are resources that will be updated periodically.

Byram Hills Documents

• Code of Conduct (Board of Education Policy 5300)
• Technology and Network Acceptable Use and Personal Privacy (Board of Education Policy 4526)

Technical Resources and Reference Documents

• MIT Teaching Systems Lab. A Guide to AI in Schools. August 2025.
• The International AI Literacy Framework. (Draft May 2025)
• Empowering Learners for the Age of AI: An AI Literacy Framework for Primary and Secondary Education. European Commission & the Organisation for Economic Co-operation and Development (OECD), Draft May 2025
• The Organisation for Economic Co-operation and Development (OECD)
• Future of Jobs Report, May 2023 (World Economic Forum)

Teaching Resources

• Code.org: Teach AI
• Google: LearnLM Tools
• ISTE: Artificial Intelligence in Education
• Common Sense Education: Courses in AI for grades 6-12