Even when incorporating the three dimensions of the Next Generation Science Standards (NGSS), there are many approaches to teaching science. These approaches depend on external factors related to the structure of the classroom and course topic and intrinsic factors based on how one teaches. What is regarded as “good science teaching” may look quite different in each context. Along with approaches to teaching, it is necessary to consider culturally relevant pedagogy (CRP), its pillars, and how it can enhance and propel student learning across all factors. Adding CRP contributes to “good science teaching” because it helps all students feel included. When the benefits of CRP are coupled with the benefits of Artificial Intelligence (AI) in teaching, our students can reap the rewards well beyond the class and this “pAIring” will impact their lifelong learning journey.

What Is Culturally Relevant Pedagogy?

First and foremost, it is important to understand the elements and characteristics of CRP that we will focus on when considering AI. CRP is an educational approach developed by Gloria Ladson-Billings (1995) that centers on recognizing students' cultural backgrounds and experiences in the learning process. It is about making learning relevant and accessible by incorporating students' culture into the curriculum and teaching methods. This approach aims to engage students more effectively, foster their academic success, and affirm their cultural identity. It is not just about understanding a student's culture, but also actively integrating it to make learning more meaningful and empowering. Integrating CRP with the NGSS is crucial because it allows students to connect their cultural experiences to scientific phenomena, which then fosters engagement, deeper understanding, and equitable learning opportunities. This pedagogy emphasizes three main pillars:

Academic Success. CRP encourages high academic expectations and achievement by building on students' existing knowledge and connecting it to new academic content. Teachers strive to help students excel academically by providing rigorous, meaningful, and culturally responsive instruction that leverages their cultural contexts.

Cultural Competence. This pillar fosters students' cultural awareness and pride in their heritage. Educators help students appreciate their cultural backgrounds while encouraging an understanding of others’ cultural backgrounds. By connecting curriculum content to students' cultural experiences, teachers can make learning more relatable and nurture a sense of belonging.

Critical Consciousness. CRP encourages students to question and challenge social inequalities and injustices. Educators help students develop a critical lens, empowering them to think analytically about societal structures and their roles within them. Through this approach, students learn academic content and the skills necessary to advocate for social change.

When the three pillars of CRP—academic success, cultural competence, and critical consciousness—are actualized through AI, students develop a stronger STEM identity and self-efficacy. AI tools make embedding CRP in the science curriculum easier, creating an inclusive learning environment that supports students’ cultural identities while promoting academic growth and social awareness. With this understanding, let’s explore the benefits of using AI and CRP together to maximize science learning in diverse settings.

AI as a Catalyst for Culturally Relevant Pedagogy in Science

With this tall order, finding ways to incorporate these pillars effectively into science lessons can be challenging. AI can be a game-changer for teaching science with a culturally relevant pedagogical approach that goes beyond simply doing a typical internet search. AI has the potential to support educators by brainstorming ideas for integrating CRP, which makes lessons meaningful and connected to students' lives.

AI can assist with accessing and summarizing data regarding an issue, such as air and water quality, and help students understand the community factors that impact water quality in their own community. This alone results in an immediate and meaningful connection between scientific phenomena and why they matter in the student’s world. For example, AI can provide comprehensive insights into water quality in specific communities such as Flint, Michigan, which had a water crisis related to lead contamination a decade ago, or Jackson, Mississippi, which has had infrastructure issues. Using AI to brainstorm potential ideas related to topics along with constraints and criteria can allow students to explore how these environmental factors affect their lives. This empowers teachers to establish meaningful connections between scientific content and real-world implications early in the learning process. By shortening the ideation phase, AI frees up time for deeper engagement with scientific topics. Research by Hadley-Hulet et al. (2024) demonstrates that AI-driven analyses of historical events, like the Industrial Revolution or the COVID-19 pandemic, can provide a backdrop for discussions on science content and how students can address community-specific challenges.

Differentiating CRP-Driven Science Instruction With AI

Once a topic has been identified, AI tools can differentiate instruction by creating personalized learning experiences that align with students’ cultural backgrounds and academic needs. Critical-thinking skills are also strengthened because when science is rigorously “tuned” to their learning “frequency,” students are motivated to learn more.

For instance, AI can do the following:

• Generate tailored questions, rubrics, and resources for different grade levels;
• Curate culturally relevant science readings to build background knowledge; and
• Provide culturally resonant examples in chemistry, biology, physics, or environmental science lessons.

By using AI-powered learning analytics, teachers can personalize resources and activities to resonate with diverse cultural perspectives. Imagine a biology unit in which students study cell structures through culturally relevant analogies, which can enhance their engagement and retention. Nazaretsky et al. (2021) emphasize that AI-based tools can support personalized instruction by analyzing students’ learning styles (auditory, visual, kinesthetic) and adapting content to their cultural and educational needs.

Evaluating CRP-Infused Science Lessons Using AI

AI can help teachers evaluate the effectiveness of CRP-based teaching. AI-generated rubrics can assess student progress and identify where additional support is needed. AI tools also can help teachers track student progress and identify areas where they might need additional support in their understanding of the content. These tools allow educators to refine teaching strategies, address misconceptions, and enhance content comprehension. By analyzing data from student assessments, AI can then recommend new teaching methods that align with CRP principles, ensuring that cultural relevance remains central to science instruction. AI can help teachers adapt current teaching strategies and adopt new strategies that can help reveal students’ misconceptions of science phenomena, which may have gone unnoticed without the CRP approach.

Benefits of AI-Driven CRP in Science Education

Ultimately, integrating AI into CRP-based science instruction can transform classroom dynamics and learning outcomes in these ways:

• Community Connections. AI can connect curriculum content to issues relevant to students' communities, thereby fostering a deeper understanding of environmental and social challenges;
• Culturally Diverse Scientific Leaders. AI can highlight the contributions of scientists from varied backgrounds, which can inspire students by representing their heritage; and
• Relatable Examples and Social Justice. AI can curate relatable problems and projects that connect scientific advancements with their impact on communities, addressing issues like environmental justice.

CRP recognizes that students' cultural identities are powerful assets in the learning process. Teachers using CRP can create inclusive science classrooms with the power of AI. CRP “pAIred” with AI can result in “good science teaching” in which students’ backgrounds are not only acknowledged, but also celebrated. This can bridge the gap between home and school cultures and make learning more relevant and accessible to diverse student populations.

References

Ladson-Billings, G. 1995. Toward a theory of culturally relevant pedagogy. American Educational Research Journal 32 (3): 465–491.

Hadley-Hulet, A., M. Ellis, A. Moore, E. Lehnardt, and M. Longhurst. 2024. Using lessons from history to guide the implementation of AI in science education. The Science Teacher 91(2): 29 –34.

Mollick, E. R., and L. Mollick. 2023. Using AI to implement effective teaching strategies in classrooms: Five strategies, including prompts. The Wharton School Research Paper. https://ssrn.com/abstract=4391243 or http://dx.doi.org/10.2139/ssrn.4391243.

Nazaretsky, T., C. Bar, M. Walter, and G. Alexandron. 2021. Empowering teachers with AI: Co-designing a learning analytics tool for personalized instruction in the science classroom. Paper presented at LAK22: 12th International Learning Analytics and Knowledge Conference.
 

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.

 

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.

Note: This article is part of the new 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.