Throughout this school year, this blog has been focusing on why and how artificial intelligence (AI) should be considered a powerful tool that can be used in the teaching of science. Used thoughtfully, AI isn’t just a tech buzzword: It’s a partner in helping students develop critical thinking. Whether it’s analyzing data, designing experiments, or exploring ethical dilemmas, AI tools can prompt, guide, and stretch students’ thinking in ways that are personalized, dynamic, and deeply engaging.

Last month, we focused on a recent report about the impact of AI on critical-thinking skills, and we discussed both AI’s role in enhancing this important aspect of learning and some of the areas that educators should be aware of. Additionally, we presented some general strategies found here for developing these skills in the age of AI.

In this month’s blog post, we offer more specific strategies for different grade levels and using different instructional modalities. As with any use of AI, it is always important for educators to ensure the accuracy of students’ responses and guide students in developing their prompts.

Strategies, Tips, and Rationales

AI and Science Learning in Elementary School

Yes! Even young learners can benefit from age-appropriate AI tools that spark curiosity and scaffold deeper thinking.

AI Strategy #1: Conversational AI for Curiosity and Inquiry

Tools like Curipod and MagicSchool.ai or child-friendly AI chatbots (like ChatGPT with guardrails) can be used to answer kids' “why” questions or help them generate their own science questions. For example, after a weather lesson, students can ask an AI, “Why do clouds float?” and get age-appropriate responses.

Teaching Tip. Have students first generate science questions that they would like to answer after reading a children’s story or seeing a video or to answer general questions they have. These questions can be posted in a particular spot in the classroom and categorized, which helps students think through their questions before they ask the AI. Use this opportunity with AI to model question generation and help students evaluate how well the AI answered and what they might ask differently. This teaches questioning and critique, which are core thinking skills.

Best For—Virtual and Hybrid classes, but easily brought into in-person discussions using a shared display.
Why It Works. Encourages metacognitive reflection—students evaluate not just the answer, but also the quality of the question and source.

AI Strategy #2: AI-Generated Observation Prompts

Use image-generating tools like DALL·E or Google's ImageFX to create mysterious science scenes (e.g., animals in strange habitats, fictional planets, odd weather patterns). Generate student discussion by asking questions like these: What do you notice? What do you wonder? Allow students to create a list of what they notice and what they wonder, and record their responses on chart paper that can be posted.

Teaching Tip. Let students generate their own image prompts based on a science topic, then swap theirs with peers to analyze them. This builds observational and inferential reasoning.
Best For—All formats. These images can be projected on a screen or shared virtually.
Why It Works. This strategy supports visual literacy and critical inference, especially for students who think spatially or creatively. This really helps students understand that different people may have different perspectives.

Best For—All formats. These images can be projected on a screen or shared virtually.
Why It Works. This strategy supports visual literacy and critical inference, especially for students who think spatially or creatively. This really helps students understand that different people may have different perspectives.

Middle School: Deeper Thinking With AI Partners

Middle schoolers are ready to tackle more abstract tasks using AI that may incorporate multiple steps. AI can provide scaffolds that encourage independence and challenge student thinking.

AI Strategy #3: Intelligent Lab Assistants

Platforms like Labster, Tynker with AI, or Exploratorium AI Labs simulate lab experiences in which students must make decisions and analyze outcomes. These platforms offer hints, ask questions, and adapt based on student input.

Teaching Tip. Teachers can pair virtual labs with reflection prompts like “Why did the AI suggest changing this variable?” or “Do you agree with the AI’s conclusion?” Students learn to evaluate reasoning from AI, which is an extremely important aspect when using this tool.

Best For—Virtual or Hybrid classes. (Ideal for limited lab access)
Why It Works. Asking students to evaluate AIs' answers requires them to access their own understanding about the topic. This approach promotes cause-and-effect reasoning and lets students learn through trial, error, and feedback, while at the same time recognizing that any information they obtain should be critically considered.

AI Strategy #4: Chatbots for Scientific Argumentation

Set up a chatbot or AI debate partner (e.g., ChatGPT in custom GPT mode) to argue different sides of a science issue—climate change, cloning, or plastic pollution. While this will require some time for first identifying resources and creating the Chatbot, it will also demonstrate for the students how AI uses information. After creating the Chatbot, students engage in the debate, which requires understanding the concept and interacting with AI’s reasoning, countering its points, and supporting their claims.

Teaching Tip. After the debate, have students reflect on these questions: “Was the AI convincing? What evidence did it use—or miss?” This builds critical evaluation skills.

Best For—All formats. Chat-based interactions thrive in online environments or face-to-face settings.
Why It Works. This strategy reinforces evidence-based argumentation and bias detection.

AI Strategy #5: Concept Mapping With AI Tools

Tools like Popplet AI, Lucidchart with AI, or MindMeister AI can help students generate and organize concepts from a unit (e.g., food webs, water cycles). The AI tool can recommend missing links, challenge connections, or ask clarifying questions.

Teaching Tip. Once a concept map is created, ask the students to have the tool challenge connections, then task the students with critiquing the AI’s suggested connections: “Does that make scientific sense? Why or why not?”  This task can be combined with asking students to generate a prompt that asks the AI tool to revise accordingly.

Best For—All instructional formats. It is great to display the maps on shared screens or in breakout rooms.
Why It Works. Using tools in this way combines systems thinking and metacognition, boosting deeper conceptual understanding.

High School: Real-World AI, Real-World Thinking

As AI is part of the future landscape, it is important to work with high school students on AI literacy skills and push them even further—by designing experiments, analyzing real-world data, and grappling with ethical questions—guided by AI.

AI Strategy #6: AI Data Analysis in Student Research

Use platforms like Google’s Teachable Machine, ChatGPT Code Interpreter, or AI4Science tools to let students input experiment data, then ask them the following: What patterns do you see? What correlations emerge? Once students have results from AI, ask them to examine the results and explain why they agree or disagree.

Teaching Tip. After analysis, students critique the model results by answering these questions: “What might this AI be missing?” or “How could you train it differently?” Another approach is to ask them to use two different AI platforms to determine if any differences or results were found and compare the outcomes produced by AI. Of course, all of these strategies require the use of good AI prompt writing. Refer to this link to assist with prompt writing.

Best For—Hybrid or In-Person classes
Why It Works. This strategy teaches data literacy, pattern recognition, and model evaluation.

AI Strategy #7: Socratic Seminars With AI Ethics Scenarios

Use AI to generate science-based ethical dilemmas (e.g., Should AI be used to predict disease risk? What communities will have access to this?). Students prep using AI-curated articles, then engage in a Socratic seminar on the implications.

Teaching Tip. Have AI serve as a silent “ghost writer” for one perspective. Students must either defend or challenge the AI's view using real science.

Best For—In-person or virtual classes (discussion forums, video calls)
Why It Works. Merges critical literacy, ethics, and evidence-based discussion—key 21st-century skills.

AI Strategy #8: Virtual Lab Journals With Reflective Prompts

Use AI journaling/notebooking tools (like Notion AI or Google Docs with Gemini) to help students reflect on lab experiences. The AI can suggest deeper questions, connect ideas across experiments, or flag reasoning gaps.

Teaching Tip. By using AI prompts like “How did today’s lab relate to your hypothesis? Did your results surprise you?” or “If you ran this again, what would you change?”, students can start to reflect on their own work and consider feedback.

Best For—All formats. Great for asynchronous reflection.
Why It Works. Strengthens metacognition, scientific reasoning, and self-evaluation.

 

Final Thought: AI Isn’t Replacing Teachers, It’s Empowering Thinkers

Using AI isn’t about replacing teachers or making the learning of science easier for students. Using AI can make students’ thinking visible. Used intentionally, AI tools can help students do the following:

•    Ask better questions.
•    Evaluate evidence.
•    Reflect on their reasoning.
•    Explore multiple perspectives.
•    Connect scientific ideas in new ways.

Whether you're guiding kindergartners through learning about weather patterns or supporting seniors designing original experiments, AI can be a catalyst for curiosity, reflection, and deeper learning.

Valerie Bennett, Ed.D., Ph.D., is an Assistant Professor in STEM Education at Clark Atlanta University, where she also serves as the Program Director for Graduate Teacher Education and the Director for Educational Technology and Innovation. With more than 25 years of experience and degrees in engineering from Vanderbilt University and Georgia Tech, she focuses on STEM equity for underserved groups. Her research includes AI interventions in STEM education, and she currently co-leads the Noyce National Science Foundation grant, works with the Atlanta University Center Data Science Initiative, and collaborates with Google to address CS workforce diversity and engagement in the Atlanta University Center K–12 community.

Christine Anne Royce, Ed.D., is a past president of the National Science Teaching Association and currently serves as a Professor in Teacher Education and the Co-Director for the MAT in STEM Education at Shippensburg University. Her areas of interest and research include utilizing digital technologies and tools within the classroom, global education, and the integration of children's literature into the science classroom. She is an author of more than 140 publications, including the Science and Children Teaching Science Through Trade Books column.

Note: This article is part of the blog series From Chalkboards to AI, which focuses on how artificial intelligence can be utilized within the classroom in support of science as explained and described in A Framework for K–12 Science Education and the Next Generation Science Standards. 

The mission of NSTA is to transform science education to benefit all through professional learning, partnerships, and advocacy.