Quick Start Guide for Integrating Generative AI Into Schools
Navigate the opportunities and risks of generative AI in K-12 education — with a practical checklist to get your district started.
Introduction
No recent topic has been more hotly discussed among K-12 educators than artificial intelligence (AI) and, in particular, generative AI. The fear among educators is that when used improperly, generative AI can subvert student learning outcomes. Not only can generative AI produce content on behalf of students, it can also hamper creative and critical thinking skill development among other considerations.
On the other hand, there are a great many benefits that can be realized by the proper use of generative AI in the classroom, by both students and teachers alike. And it’s that age-old paradox, the potential “good” versus “evil” that has educators so split on the use of generative AI tools.
Try as a great many might, generative AI is not going away. The genie is out of the bottle, so to speak, and it’s here to stay. It’s up to educators and edtech solution providers to determine the most effective way to tap into the technology’s potential while, at the same time, mitigate its very real risks.
This eBook is designed to help K-12 school districts navigate the still choppy waters of generative AI in education. It will guide you through the definition of generative AI, how it works, and its capabilities and limitations. Most importantly, it will provide you with an actionable checklist to effectively integrate generative AI into your district.
01 | Overview: What is Generative AI?
Generative AI is a form of artificial intelligence that learns from existing data to generate new content that reflects the characteristics of its training data but does not repeat it. As a result, generative AI produces a wide variety of new content, including images, videos, music, speech, text, software code, and product designs.
Some of the most popular generative AI tools for educators and students are ChatGPT, GPT-4, Bard, and the AI video platform, Synthesia, among others.
Not all AI tools used in school districts are generative AI applications. Predictive AI applications can analyze patterns in student data to forecast expected outcomes, such as being on track for promotion or graduation, for example. Those outputs allow educators to develop data-driven insights and proactively intervene as required.
02 | How Generative AI Works
Generative AI begins with a prompt. ChatGPT, for instance, responds to conversational text prompts to generate new content. Prompts for other solutions take the form of text, image, video, design, musical notes, or any input that the system processes.
Large language models (LLMs) then take over. Those LLMs, like the ones driving chatbots like ChatGPT, have been trained through deep learning algorithms to recognize, generate, translate, and summarize enormous quantities of written language and textual data.
After ingesting the original prompt, the generative AI platform’s algorithms deliver its new content in any of several forms, including essays, mathematical solutions, or even “deep fake” videos. New features in the quickly evolving space now allow users to refine initial results with feedback about the style, tone, voice, and other elements they want any subsequently generated content to reflect.
Generative AI begins with a prompt.
03 | Understanding Generative AI's Capability & Use Cases
Much of the discussion on generative AI centers on better understanding the technology’s abilities and limitations—what it can and cannot do. Those conversations tend to naturally evolve into the potential benefits and risks inherent in the technology’s use.
Potential benefits of generative AI to school districts include:
- Content ideation and development
- Personalized assessments, tutoring, and learning assistance
- Quick and timely feedback to students/parents
- Administrative efficiencies
The potential application of generative AI in education appears seemingly endless. Perhaps the most promising aspect is the potential to create personalized, interactive learning content and experiences for each student.
A few of the many potential use case examples include:
- Generate questions based on an individual student’s current level of understanding or achievement.
- Deliver real-time feedback and assessments, empowering both teachers and students to identify individual strengths to leverage, opportunities to improve, and any additional supportive needs required.
- Create personalized, adaptive lesson plans based on a student’s assessed level of aptitude and performance.
- Develop interactive learning activities, including simulations and games, to engage students on a particular subject.
- Provide step-by-step hints and suggestions to accelerate a student’s problem-solving and learning on an assignment.
- Generate email and other messages for teachers to send to students, parents, and administrators.
Related to teaching resources, generative AI has the potential to act as a teacher’s virtual assistant, delivering individualized, real-time feedback and expanding the teaching capabilities at every educational level.
The most promising aspect is the potential to create personalized, interactive learning content and experiences for each student.
04 | Understanding Generative AI's Limitations & Challenges in K-12 Education
Of course, the flipside of generative AI’s benefits to educators is the technology’s limitations, challenges, and perceived threats.
Like all new technologies, generative AI also arrives with its fair share of limitations, challenges and potential for abuse, and concerns to school districts include:
- Plagiarism and academic dishonesty
- Compromised student data privacy and online safety
- Perpetuating and further strengthening societal bias
- Loss of critical thinking and reasoning skills due to overreliance on AI tools
- Exacerbate the existing ‘digital divide’ and prevent digital equity among students
A primary concern lies in the potential for bias in generated educational content, as an AI app’s algorithms are only as good—and as unbiased—as the data on which it is trained. Perhaps nowhere does the old data science/data processing warning of “garbage in, garbage out” resonate more than with generative AI. If a tool is trained with biased data inputs, educational outputs will be created that perpetuate or even amplify stereotypes or prejudices. And, with its outputs consumed as additional inputs, the bias cycle perpetuates.
Then, of course, the digital divide between students with and without ready access to technology may be destined to widen by generative AI in education, adversely impacting underserved and minority students. There’s also the standing threat of a student’s data security, privacy, and online safety.
However, the biggest challenge of generative AI in education might be the threat of unethical use of the technology.
Naturally, plagiarism, the practice of taking someone else’s work or ideas and passing them off as one’s own, is a dominant concern. But the challenge of generative AI as a crutch goes much deeper, with the threat of students relying too heavily on the technology to provide immediate answers stunting their ability to think critically and solve problems.
The biggest challenge of generative AI in education might be the threat of unethical use of the technology.
05 | How Generative AI is Currently Being Utilized in K-12 Education
Currently, school districts are split as to the use and misuse of generative AI. At one end of the spectrum, some schools take a zero-tolerance approach, associating the use of generative AI tools with plagiarism. In that situation, districts deploy AI detection tools to identify instances when students deliver AI-generated assignments.
At the far other end of the spectrum are schools that work to integrate generative AI applications to support and further accelerate student learning. Rather than investing time and other resources in identifying misuse, teachers and other faculty work collaboratively to collectively understand the benefits, limitations, responsible use cases, and potential threats in using generative AI in school.
The generative AI debate continues, but in practice, most school districts have taken a hard stand against the tools. According to aggregate data pulled in October 2023 from the over 28,000 schools that deploy Lightspeed Filter™, over 92 percent of schools have blocked access to the most popular generative AI tools.
As of 2023, according to aggregate data from over 28,000 schools, 92% have blocked access to the most popular generative AI tools.
Naturally, blocking access, both on-campus and with school-issued devices, isn’t a long-term solution, as generative AI applications are not going to go away. Ever. At best, the current situation is a temporary measure as school districts evaluate how best to integrate generative AI technology into curricula and classrooms.
06 | Integrating Generative AI in K-12 School Districts
School districts can no longer delay integrating generative AI applications. Simply, teachers and students already have independent access to a great many AI tools, including, among others, systems that integrate AI, like search engines and email platforms.
Below is a checklist to effectively incorporate generative AI applications into K-12 school systems and promote critical learning outcomes.
07 | Summary
Education has always been a noble, innovative profession, one quick to adapt to new tools and methods. Just as the availability of advanced scientific calculators over forty years ago caused a stir in math departments around the world, generative AI sparks similar concerns throughout schools.
However, just as scientific calculators didn’t go away, neither will generative AI applications—the technology is destined to become a staple in everyday life, including schooling and on the job.
To successfully integrate generative AI into schools, educators must fall back to their single-most guiding principle whenever making changes: enhancing learning experiences and producing better student learning outcomes.
Utilize the framework in the proceeding pages to effectively integrate generative AI into your school districts, facilitating learning and reducing administrative inefficiencies. Furthermore, please find additional resources on the very next page.
08 | Additional Resources
Establishing Generative AI Guidelines and Policies
- K-12 Generative AI Readiness Checklist, Council of the Great City Schools and Consortium for School Networking (CoSN), 2023.
- The Ethical Framework for AI in Education, The Institute for Ethical AI in Education, 2023.
- Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations, Office of Educational Technology, United States Dept. of Education, 2023.
- Guidance for generative AI in education and research, United Nations Educational, Scientific and Cultural Organization (UNESCO), 2023.
- Setting Conditions for Success: Creating Effective Responsible Use Policies for School; International Society for Technology in Education (ISTE), Consortium for School Networking (CoSN), Digital Citizenship Coalition, and Association of Technology Leaders In Independent Schools (ATLIS), 2023.
- “Off Task: EdTech Threats to Student Privacy and Equity in the Age of AI,” Center for Democracy and Technology, 2023.
Teaching and Learning with Generative AI Applications
- “Strategies for Teaching Well When Students Have Access to Artificial Intelligence (AI) Generation Tools,” George Mason University, 2023.
- “Promoting Academic Integrity in Your Course,” Center for Teaching Innovation, Cornell University, 2023.
- “Citation, Documentation of Sources,” Chicago Manual of Style, 2023.
- “How do I cite generative AI in MLA style?,” MLA Style Center, 2023.
- “How to cite ChatGPT,” APA Style, 2023.
