Two Types of AI Tools Used in Schools

Generative AI tools can create text, code, and other types of content. However, using them to complete assignments can raise issues of plagiarism.

Predictive AI tools analyze patterns in student data to forecast outcomes such as being on track for graduation. These insights allow educators to intervene proactively but require care in understanding outputs and evaluating them for potential bias.

Other uses of AI include

• Intelligent tutors to provide personalized teaching.
• AI for assessment to augment grading efficiency and consistency.
• Assisting with administrative tasks such as scheduling.

Want to learn more about AI?

• See the AI in Education Presentation. Download the slides to customize your own presentation.
• See ISTE’s AI resources, including Tips for School Leaders.
• See AI 101 for Teachers from Code.org, ETS, ISTE, and Khan Academy. 

This toolkit serves as an initial step in guiding the safe, effective, and responsible use of AI in education.

The landscape of AI in education is evolving rapidly, and as new technologies mature, use cases emerge, and the understanding of AI's impact deepens, guidance will need to adapt. 

This toolkit is designed to help education authorities, school leaders, and teachers 

create thoughtful guidance to help their communities realize the potential benefits of incorporating artificial intelligence (AI) in primary and secondary education while understanding and mitigating the potential risks. ​

With guidance, an education system may realize the potential benefits of AI to improve learning outcomes, support teacher instruction and quality of life, and enhance educational equity. Without guidance, teachers and students can be exposed to privacy violations, inconsistent disciplinary consequences, and counterproductive AI adoption practices.

This toolkit is designed to help local, state, and national education systems worldwide develop guidance on the responsible use of AI, ensure compliance with relevant policies, and build the capacity of all stakeholders to understand AI and use AI effectively. The recommendations in this toolkit may also inform the early stages of developing policies and procedures, whether mandatory or voluntary.

While issuing standalone guidance on AI can be an initial step, it’s also important to consider how and where it makes sense to address AI in existing policies, such as academic integrity, privacy, or responsible use policies. Guidance and policies will benefit from the input and review of various stakeholders, including teachers, parents, and students.

Guidance and policies should be developed in accordance with an education system’s established policy development process, which may include a review by a policy committee, key stakeholders (e.g., teachers, parents, and students), and legal counsel before seeking approval from governing bodies.​

How to Use this Toolkit​

A Framework for Incorporating AI in an Education System

Create guidance and policies to address immediate issues 

Compared to the introduction of previous technologies in education, education systems should not delay efforts to develop guidance on the use of AI since students and teachers already have independent access, and many existing technologies embed AI into their systems (e.g., search engines and email applications). The first step should be ensuring that AI use complies with existing security and privacy policies, providing guidance to students and staff on topics such as the opportunities and risks of AI, and clarifying responsible and prohibited uses of AI tools, especially uses that require human review and those related to academic integrity. 

Facilitate organizational learning​

In parallel with guidance and policies that address immediate concerns, education systems must prioritize professional development for all staff and bring together individual educators' experiences with AI to document successes, identify gaps, and build collective organizational knowledge and capacity. A systemwide approach would go beyond instructional issues to include operational considerations such as evaluating AI tools already in use and creating selection criteria for future evaluations. It also leads to more equitable AI integration across classrooms and prevents inequities from emerging when innovation diffuses haphazardly.

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 In May 2023, the Ministry of Education in Chile released a teacher guide called How to Use ChatGPT to Enhance Active Learning. The guide provides a variety of use cases and prompts and covers key limitations and precautions.​

“At the current time, as a country, we need to enhance the learning of all students to be able to face the challenges of today's world - and an uncertain future - and support teachers to achieve these objectives. In this context, we must prepare educational institutions, teachers, students, and families to take advantage of the opportunities offered by new technologies and act against their risks.”

Thoughtful guidance and effective organizational learning set the stage for AI to contribute to improvements and transformations across a system. These transformations may include competency-based education powered by personalized learning, project-based learning aided by real-time and augmented feedback, and more time for teachers when AI is used to streamline administrative tasks. Incorporating AI into education provides an opportunity to expand evidence-based reforms, provided policies exist to support fair implementation, and there are investments in organizational learning. ​

Promote improvement and transformation

Responsible Use Policy

A responsible use policy, also known as an acceptable use policy or technology use policy, describes the terms and conditions of technology use in an educational institution. These existing policies should be updated to ensure all users use AI tools safely and appropriately. For more information, see Setting Conditions for Success: Creating Effective Responsible Use Policies for Schools.​

Engage with TeachAI partners and others, such as Code.org, CoSN, Digital Promise, ISTE, and UNESCO, for timely access to guidance, 

frameworks, and other resources. Visit the resources section.

These three stages – Policy, Organizational Learning, and Improvement and Transformation – provide a framework for incorporating AI across a system where guidance and policy development advance hand in hand with organizational learning, and both transition from a focus on addressing current concerns with AI to using AI to transform the educational system.​

Welcome

Real-World, Concrete Examples

The toolkit illustrates potential approaches rather than definitive models and provides examples of AI guidance from local, state, and national education systems. The toolkit also has a section that organizes sample AI guidance considerations for responsible use policies, privacy policies, and academic integrity policies. The examples and suggestions are not meant to be copied verbatim but to anchor understanding in practical examples and prompt thoughtful discussions about developing AI guidelines. The examples and sample language can be considered starting points to inform each education system’s own process of responsibly shaping AI guidance, policies, and practices.

Please provide feedback on the toolkit, including how you have used it. Your responses can inform ongoing updates and provide lessons learned and examples for ongoing learning and sharing.

AI Guidance for Schools Toolkit © 2023 by Code.org, CoSN, Digital Promise, European EdTech Alliance, and PACE is licensed under CC BY-NC-SA 4.0