Introduction
In recent months, research-based and popular media articles have emerged related to critical-thinking skills and artificial intelligence (AI) (Jackson 2025). This is not a new topic and has been discussed for many years as AI platforms have been developed and trained; however, recently the focus has been on how AI impacts the user’s critical thinking. In full disclosure, many of these headlines are related to the use of AI in the business setting; however, some are now examining the same points as they relate to AI in classrooms. This blog post focuses on recent discussions and research findings to explore how AI affects critical thinking, examining both the potential benefits and the challenges it presents.

One of the most recently cited studies in this area comes from Microsoft (2025), which focused on knowledge workers and their perceptions of where and how critical AI impacts thinking. The simplified “spoiler alert” from the study’s abstract reads as follows: The higher the level of confidence in AI that the user has, the lower the critical thinking (inverse correlation), while the higher a user’s self-confidence is, the greater their use of critical thinking (direct correlation). Figure 1 shows these relationships. This leads to posing these questions: How does AI impact the development of critical-thinking skills in science? How can teachers best use AI while developing those exact skills?

AI's Role in Enhancing Learning and Critical Engagement
As with any educational tool or strategy, there are multiple perspectives. Proponents of AI in education argue that these technologies can enhance learning experiences by automating routine tasks, thereby increasing the time students focus on higher-order cognitive activities. Some ways that AI use can free up time to engage in the more complex tasks can be assisting students in creating podcasts from readings, summarizing documents, and writing code. Such applications are believed to foster deeper engagement and critical analysis among students. Students also gain practical skills for the workplace, especially in handling AI, which rapidly evolves and improves.

Concerns About Overreliance on AI and Diminished Critical Thinking
Despite the potential benefits, there is growing concern that excessive dependence on AI may erode critical-thinking skills. Studies have indicated that when individuals rely heavily on AI for information retrieval and decision making, their ability to engage in reflective problem solving and independent analysis may decline. Example studies include one published on Phys.org (2025) that addressed cognitive offloading or transferring mental effort to external aids. The study’s authors reported a significant negative correlation between AI tool usage and critical-thinking scores. One important note from this study was that younger participants (ages 17–25) showed higher dependence on AI tools and lower thinking scores than older age groups did. These findings need to be considered as they relate to education and AI use in the classroom.

A recent study published on Phys.org highlighted a concerning trend: Students who frequently rely on AI tools show lower critical-thinking scores. While offloading simple calculations to a tool like a calculator is practical, excessive reliance on AI for complex reasoning tasks could weaken students’ ability to think analytically and solve problems independently.

In science education, this reliance could mean students bypass the essential cognitive struggle of forming hypotheses, analyzing results, and drawing conclusions—skills fundamental to scientific investigation, design thinking, or the engineering design process.

The Double-Edged Sword
The integration of AI into educational settings presents a paradox. On one hand, AI can serve as a powerful tool to enhance learning, providing personalized feedback and automating mundane tasks. On the other hand, there is a risk that students may become overly reliant on AI, leading to a decline in critical-thinking and problem-solving skills. The challenge for educators is to determine where and how to integrate it so that it aids students in the previously mentioned tasks while simultaneously helping to develop their thinking skills.

Strategies for Fostering Critical Thinking in the Age of AI
To find the recommended key balance, teachers will need to leverage AI effectively for some tasks while fostering critical-thinking skills in others.

1. Promote Active Engagement With Scientific Data
Rather than letting AI generate answers, ask students to interpret AI-generated data themselves. Also within this area, ask students to engage in hypothesis testing through additional research and evidence-based reasoning and determine if they see emergent patterns. If planned properly and modeled for the students so that they can practice this type of use, AI becomes not just a source of information, but also a means of engaging with scientific inquiry on a deeper level. An example would be taking a typical lab or assignment and having students find data to support or refute an argument about what they found. This data gathering could be related to water safety, diseases, or pathogen rates where they live.

2. Use AI to Facilitate Scientific Argumentation
Encourage students to use AI as a tool to gather evidence for debates or scientific arguments. Ensure that students then “fact check” the information that was provided for accuracy. A second strategy would be to provide AI with information—i.e., a map of a path that a hurricane is on—and then present two explanations for the path, one that is meteorologically accurate (always double-check yourself) and one that is plausible, but inaccurate. Provide these explanations to the students and ask them to determine which one is on target and why.

3. Require the Use of Claim, Evidence, and Reasoning (CER)
Phenomenon-based learning places students in the role of scientists, encouraging them to ask questions, form hypotheses, and conduct experiments. AI can support this by offering dynamic simulations and interactive environments where students can test their ideas or even provide potential explanations for a phenomenon. Students should still be asked to critically evaluate any information that is AI-generated and explain their own reasoning for an answer.

4. Frame AI as a Resource, Not a Shortcut
By framing AI as a resource for exploration rather than a shortcut to solutions, teachers can help students maintain an active role in their learning process. Instead of using AI to provide direct answers, educators can encourage students to use AI as a discussion partner. For example, students can use AI-generated data as a starting point for class debates or group projects. This promotes collaborative problem solving and requires students to evaluate, question, and interpret the information AI provides. Pose thought-provoking questions to students regarding the data, such as “Are there any biases in the data? What are the sources of this data?”

AI as a Catalyst for Scientific Critical Thinking
The use of AI presents both opportunities and challenges in teaching critical thinking in science. While there are reports on and a need to consider the concern about the pitfalls associated with AI, thoughtful integration of AI into science curricula can actually enhance inquiry-based learning and foster higher-order thinking. It is important to be strategic when and how you introduce AI tools when helping students develop critical-thinking skills. Any incorporation of tools should be thoughtfully planned so it does not hinder the great work you have already started in your classroom to develop these skills. For example, consider how AI can be used to enhance three-dimensional learning as described in an earlier blog post [https://www.nsta.org/blog/empowering-science-education-ai-enhancing-three-dimensional-learning].

The key is balance. AI must complement—not replace—the intellectual engagement that drives scientific discovery. By thoughtfully integrating AI, science educators can cultivate classrooms in which technology enhances curiosity and critical thinking thrives—a space where the next generation of scientists, innovators, and critical thinkers can flourish.

References
Jackson, J. 2025, January 13. Increased AI use linked to eroding critical thinking skills. Phys.org. https://phys.org/news/2025-01-ai-linked-eroding-critical-skills.html. 

Lee, H.-P., A. Sarkar, L. Tankelevitch, I. Drosos, S. Rintel, R. Banks, and N. Wilson. 2025. The impact of generative AI on critical thinking: Self-reported reductions in cognitive effort and confidence effects from a survey of knowledge workers. In CHI Conference on Human Factors in Computing Systems (CHI '25), April 26–May 1, 2025, Yokohama, Japan. ACM. https://www.microsoft.com/en-us/research/wp-content/uploads/2025/01/lee_2025_ai_critical_thinking_survey.pdf.  

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 Through Trade Books column.

 

Valerie Bennett, Ph.D., Ed.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 NSF grant, works with the AUC Data Science Initiative, and collaborates with Google to address CS workforce diversity and engagement in the Atlanta University Center K–12 community.
 

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.