Incorporating Generative AI in High School Classrooms: A Deep Dive into Using ChatGPT and Similar Tools

As the school year gave way to summer, I found myself in a lively discussion with fellow educators about ChatGPT in our daily lives. The consensus? The robots are indeed here, but instead of a bleak, science fiction-inspired future, we envisioned our interactions with generative AI resembling one of Michael Scott’s quirky, albeit misguided, ventures into the realm of computers on “The Office.” After some robust laughter, our conversation took a serious turn—how do we bring this transformative technology to our students in the classroom?

How do we teach students to use ChatGPT and other generative AI tools effectively and responsibly?

One technology in the ever-evolving digital landscape has consistently made headlines and transformed industries: Artificial Intelligence (AI). A particular branch of AI, called generative AI, is revolutionizing how we interact with technology and has made us rethink the future of education. Experts are already mapping it out.

One remarkable example of generative AI is ChatGPT, a state-of-the-art generative language model developed by OpenAI. ChatGPT’s public release after Thanksgiving of 2022 shook the world with a broad spectrum of curiosity and concern. As educators, we must equip our students with an understanding of this groundbreaking technology and not just about ChatGPT.

Preparing students for their futures, which AI and advanced technologies will undoubtedly shape, requires us to collectively embrace these evolving technologies to teach students how to use these tools ethically and effectively.

Understanding Generative AI and ChatGPT

Generative AI is a subset of AI that focuses on creating something new. Instead of simply analyzing and learning from input data, generative AI can generate novel content, often from user-generated prompts and input requests. Outputs from these models can range from text to images and audio, including music and even realistic human speech. Generative AI operates on the foundations of machine learning and neural networks, two core concepts in the AI world.

ChatGPT is a large language model that utilizes a sophisticated form of machine learning called deep learning. Trained on vast amounts of internet text, ChatGPT can produce human-like responses based on the inputs it receives. “GPT” in ChatGPT stands for “Generative Pre-training Transformer”:

• Generative refers to the model’s ability to create or generate contextually relevant data.
• Pre-training means the model’s trained on a large dataset (mostly text) to understand human language.
• Transformer references the type of computer neural network used to generate the human-like speech output.

Students need to understand this rudimentary element of what GPT stands for to use and effectively appreciate ChatGPT’s capabilities and limitations.

The goal of ChatGPT is not simply to mimic human conversation but to provide a useful and meaningful interactive tool that can assist in a wide range of tasks. Many educators and students are already finding uses—from lesson plans and generating questions to writing, editing, and basic coding.

The Importance of Learning about Generative AI

The significance of generative AI, especially in the rise of large language models (LLM) like ChatGPT, cannot be understated. Generative AI tools are growing more ubiquitous and powerful, finding use in many sectors, including entertainment, healthcare, education, and business. Understanding generative AI is no longer just beneficial for computer scientists or tech professionals; it’s becoming a vital skill for everyone as our future workforce will evolve with this technology.

For high school students, learning about generative AI and tools like ChatGPT can offer invaluable insights into the technology shaping their world. Moreover, as these students prepare to enter the workforce, a foundational understanding of AI can open doors to many career opportunities in the tech industry and those outside who will use AI to make their work more efficient.

By incorporating generative AI concepts into our curriculum, we are not just teaching students about technology—we are preparing them for a future where AI plays an increasingly integral part in everyday life. AI already does so much for us today with autocorrect, facial recognition, and producing social media feeds. This is why learning about generative AI, specifically models like ChatGPT, is critical for today’s students.

Generative AI Lesson Plans: Core Concepts

Much like teaching students how to use a graphing calculator, a 3D printer, or even a graphic organizer, students need to understand how to operate these tools if they are to use them effectively. However, for AI, teachers should highlight the key foundational concepts of generative AI. A deeper understanding of these principles will allow students to appreciate the potential and inner workings of models like ChatGPT.

Below are several concepts and examples to guide student understanding:

Machine Learning (ML):

Machine Learning, a subset of AI, centers on teaching computers to learn from data without explicit programming. Students need to grasp a basic understanding of ML because it forms the backbone of generative AI.

One common example of ML is an email account spam filter or junk folder. The program learns from data—features of emails marked as “spam” or “not spam”—to predict and filter out future spam emails. Another example involves teams at institutions like MIT developing AI programs to learn video games like Super Smash Bros. to take on human challengers.

Neural Networks

Inspired by how the human brain functions, neural networks are a series of algorithms trained to process data similar to how the human brain interprets sensory inputs. Neural networks, particularly “deep” neural networks with many layers, are essential to generative AI models like ChatGPT.

One basic example is image recognition, like your phone’s ability to recognize your face and that of others for tagging or security purposes. This ability comes from a neural network trained to identify faces and distinguish them by distinct traits accumulated from more and more photos. Another example includes photographing hand-written notes to convert into digital text formats. In this process, a neural network learns how to identify the distinct attributes of diverse handwriting.

Natural Language Processing (NLP)

NLP is the technology used to give computers the ability to understand, interpret, generate, and respond to data in a way that mirrors human language. Essentially, it’s training artificial intelligence in the field of linguistics. It’s central to language models like ChatGPT and is vital for students to understand how AI interacts in human-like ways.

By understanding these core concepts of AI, students will gain a more holistic view of generative AI and how they can utilize it. Moreover, these principles are crucial not only for potential careers in AI and tech but also for other fields that increasingly intersect with AI, such as healthcare, business, and even the arts. As educators, our role is to make these complex concepts accessible and engaging to empower the next generation with AI literacy.

Teaching Generative AI Through ChatGPT-centered Activities

To successfully engage students with generative AI and tools like ChatGPT, we must understand their functionality’s key elements. One tactic involves a “hands-on” approach by blending the what and how-to of these tools—leading to practical and creative classroom activities, fostering hands-on learning experiences, and critical metacognitive activities.

Introducing ChatGPT to students offers a revolutionary way to engage them in learning. Unlike traditional search engines, which return a list of websites based on keywords, LLMs like ChatGPT are equipped to process and generate human-like text, making learning more interactive and individualized to students based on their input prompts.

Search engines excel in locating specific information across the internet, and so programs like Google and Bing are still essential for students’ day-to-day learning. LLMs, however, stand out in their ability to maintain engaging, multi-turn dialogues. LLMs reference previously entered context, enabling real-time, meaningful conversations like speaking to a knowledgeable person. This level of interactivity can stimulate critical thinking in students as they probe complex topics and can allow students a more individualized learning experience.

Input-Prompt-Based Activity

ChatGPT generates responses based on an input prompt. Well-crafted prompts will help students become more proficient and efficient with the tool. At the moment, most experts agree on five key components of a well-structured prompt:

1. Defining the role or area of work the chat will focus on
2. Provide context or relevant background information
3. Clearly state the ask or task at hand
4. Establish limitations by describing what can and cannot be considered
5. Offer additional guidance or references

Consider creating an activity where students can experiment with different prompts using the structure above. Have students observe and evaluate the variety of responses generated by ChatGPT, especially as they play with other aspects of the prompt structure. This engineering activity can be ludic and collaborative in its design by asking students to be creative and critical of their development.

Pattern Recognition, not Conscious Understanding

Students should understand early in their exploration of generative AI tools that they operate based on recognizing and predicting patterns from data they’ve already been trained on. These tools do not possess understanding or consciousness.

Despite the human-like text it generates, generative AI is a tool and not a sentient being. It’s improbable that programs like ChatGPT will be as creatively unique as human students.

One way to teach students about this concept is to organize a prediction-style activity. Students will quickly realize that ChatGPT operates based on recognizing and predicting patterns rather than a conscious understanding. Consider using the prompts they’ve already developed and have students adjust one parameter. Encourage students to make predictions based on their adjustments and then reflect on them.

No Memory or Continuity Activity

Unlike humans when engaged in conversations, ChatGPT doesn’t hold a working memory. Instead, a previous context within a chat thread is prepended (attach data to the beginning of another) with each new prompt as you hit submit. This means the chat is limited to only so much context before entirely forgetting earlier content. Therefore, providing too much information will limit the response of ChatGPT, making it shorter and hyper-focused on the more recent prompt.
I have explored this activity numerous times to understand more about how to shape prompts and expectations. First, have students establish a goal:

“I will have ChatGPT accomplish this for me…”

Next, create a series of quick, easy-to-develop prompts to converse with ChatGPT. From there, continuously change aspects by adding and adjusting the context.

Prompt: You’re a student learning about the history of artificial intelligence. Develop an expository essay describing the history of generative AI. Be sure the essay is under 500 words and is written in a language a middle school student can understand.

Adjustment: You’re a teacher researching the history of artificial intelligence. Develop a conference paper describing the history of generative AI and neural network construction. Be sure the essay is under 800 words and is written in a language other educators can understand.

As students introduce new prompts, have them identify when information is no longer included or relevant to their initial goals or when the response is not of the same quality as previous outputs. Think about the game Jenga—as you remove and stack a single block, the tower can grow incredibly high but will become more unstable.

Teaching Students About Effective Generative AI Use

The Power of Tuning

A further step towards helping students understand the working memory of programs like ChatGPT, as well as the accuracy and relevance of its generative outputs, depends on how students fine-tune their input prompts and interactions. Like editing and proofing writing, students should understand how tuning and revising can create better outputs or influence hallucinations or unexpected responses.

Hallucinations and Inaccurate Information

Arguably the most important aspect to teach students, ChatGPT is a tool for people to use and is, therefore, just as subject to human error. Many have learned about “hallucinations” and wild responses from the model, so teachers need to help students understand how generated responses could include plausible but factually inaccurate and nonsensical information.

ChatGPT cannot access real-time information unless you’re using plug-ins or third-party apps. Instead, it generates text based on patterns learned from the broad dataset it was trained on. For ChatGPT3.5, the current version available for free, that dataset cuts off in June of 2021. If asked about a specific event, even one that occurred before the training data was collected, or asked to provide personal experiences, it could “hallucinate” a response that seems plausible but is entirely untrue or inaccurate.

Integrating the Four Cs of Digital Literacy with Generative AI

In the digital age, the Four C’s of Digital Literacy—Critical Thinking, Creativity, Communication, and Collaboration—are essential literacy skills for students to succeed in the future.

We’ve identified these skills as valuable competencies in two of our XQ Learner Outcomes—Original Thinkers of an Uncertain Future and Generous Collaborators for Tough Problems. Our XQ Learner Outcomes are a series of research-backed skills and outcomes that outline what students should know to be successful in college, career, and whatever the future may hold. 

Here’s how these skills connect to AI literacy, particularly when using generative AI in the classroom:

• Critical Thinking—Teaching students to analyze and evaluate AI-generated information enhances critical thinking skills. Have students discern between reliable and unreliable AI outputs, an increasingly important skill set as AI becomes more pervasive in society.
• Creativity—With AI like ChatGPT, students can leverage their creativity in new ways. Whether generating novel content, designing unique AI interactions, or problem-solving with AI, integrating AI in classrooms inspires a new dimension of creativity.
• Communication—Effectively expressing one’s thoughts is crucial in the digital age. Students can focus on their communication skills when interacting with AI as they practice drafting and editing. Combined with metacognitive activities, students can reflect on how the chatbot, and other models, read and respond to their writing.

Using AI in the classroom helps boost digital literacy and prepares students for a future where integration will increase in daily life. This digital empowerment fosters key learning outcomes to help students become active contributors in the evolving digital landscape.

Teaching Students About the Ethics & Safety of AI

AI businesses and industries have outlined and implemented various safety measures like content filters to limit inappropriate or harmful output. But the system isn’t perfect, and students should be aware.

Concerns with ChatGPT and Student Plagiarism

Plagiarism is often a paramount concern for educators, and this concern persists regardless of the use of generative AI. It’s crucial to remind students that plagiarism is unacceptable, including content produced by AI. Typically, plagiarism can indicate deeper issues students grapple with, such as self-doubt or challenges in executive functioning.

Rather than viewing AI as a source of content, we should position it as a facilitator for learning activities. Generative AI can serve as an excellent tool for brainstorming and revising work, aiding in conceptualizing and refining ideas. Additionally, it’s important to review and emphasize the correct method of citing materials, including those generated by AI programs. This ensures academic integrity and helps students responsibly maximize AI’s educational potential.

While teaching students about LLMs like ChatGPT, it’s equally important to guide them through AI tools’ ethical and safety aspects. Data, privacy, and ethics are larger conversations beyond just one subject. But below are several approaches specific to generative AI:

• Data Privacy—As LLMs generate text based on input, students need to understand why it’s important not to provide any sensitive personal information while interacting with these models. Understanding the broader principle of data privacy is vital for all students and educators in our digital age.
• AI and Bias—Teach students about the potential for AI systems to reflect and even amplify societal biases present in the training data, especially given that many of these models are trained on current information published online. Encourage students to critically evaluate AI-generated content for any potential bias.
• Responsible AI Use—Students should be encouraged to use AI responsibly, understanding that AI tools can be misused to generate inappropriate, harmful, or misleading content. Guide students towards ethical practices while using AI; refrain from using AI to deceive others through plagiarism, spreading false information, or generating content to use against or harm another individual.
• Content Filtering and Safety Measures—Lastly, students should know about the safety measures implemented by organizations such as OpenAI, including content filtering, to limit the generation of inappropriate content. However, consider how you can include students in identifying how to create a safe and inclusive learning environment when using generative AI.

Making ethics and safety a central part of AI education prepares students to use AI tools effectively and navigate the evolving digital landscape responsibly and conscientiously.

By integrating the understanding of these elements into hands-on activities, we can help students comprehend how to use ChatGPT effectively and grasp the broader principles of AI. These valuable skills will prepare students for the future, fostering an in-depth understanding of technology, promoting creativity, and encouraging critical thinking about the benefits and challenges of AI.

AI businesses and industries have outlined and implemented various safety measures like content filters to limit inappropriate or harmful output. But the system isn’t perfect, and students should be aware.

Conclusion: Where Educators Can Go with Generative AI

As we forge ahead in this AI revolution, how we integrate artificial intelligence and generative AI in classrooms is not just a possibility—it’s an inevitability. Using generative AI in the classroom, such as tools like ChatGPT, will empower students with a powerful and interactive learning experience. Students can become proficient and responsible AI users by understanding core concepts of generative AI and recognizing large language models’ capabilities and limitations through hands-on activities.

Ensuring students grasp critical concepts such as AI hallucinations, data privacy, and AI’s potential for bias is essential to fostering AI literacy. This ties directly to the Four C’s of Digital Literacy—Critical Thinking, Creativity, Communication, and Collaboration—equipping students with the skills necessary to navigate and contribute to an AI-driven world.

As educators, we need to prepare our students for this future. We must equip them with the knowledge to use generative AI tools like ChatGPT effectively and understand the ethical and safety considerations surrounding them. The goal is to create a learning environment where students participate actively in the digital landscape and are not just passive consumers.

Photo at top by: Chris Chandler

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