With two decades of experience teaching STEMM, LabXchange teacher-in-residence Angela Campbell has been working alongside instructional designers to create content for a new LabXchange initiative entitled Artificial Intelligence & Data Literacy. This new initiative will produce high-quality, interactive, and modular digital content for self-directed learning and classroom instruction at the high school level.

In addition to providing an introduction to the fundamentals of data science and AI technology, the content will cover the intersection of data, society, and ethics; the data lifecycle; computational and statistical foundations; machine learning and modeling; and collaborative and advanced practices in data science. By focusing on experiential learning with both real and simulated datasets, the resources will empower learners with data acumen and critical thinking skills to be informed citizens prepared to succeed in college and beyond.

In the interview below, Angela explains the real impact that AI is having on educators and learners, the importance of data literacy beyond the classroom, and the reasons why LabXchange is placing renewed emphasis on creating data science resources.

Why is it important to create AI and data literacy content for classrooms?

Artificial intelligence and data literacy are rapidly becoming essential components of how we understand and interact with the world. Bringing this content into classrooms ensures that students are not just passive users of technology, but informed participants who can question, analyze, and apply it responsibly.

How are educators being impacted by AI? And learners?

Educators are navigating a significant shift in both instruction and assessment as AI tools become more widely used. This shift is prompting a reexamination of how assignments are designed, how understanding is measured, and how critical thinking is fostered. For learners, AI presents valuable opportunities for personalized learning, but it also demands stronger skills in evaluation, ethical use, and interpretation. At the same time, teachers are working to ensure that student work reflects authentic understanding, not simply AI-generated responses. In some cases, this has led educators to incorporate more traditional, paper-based assessments alongside digital tools to better gauge individual learning.

How will the AI & Data Literacy initiative help educators teach learners about data science?

LabXchange’s growing collection of AI and data literacy resources provide educators with ready-to-use, standards-aligned materials that make complex concepts more accessible. By integrating AI and data literacy into familiar subject areas, it lowers the barrier for teachers who may not have a background in computer science while still maintaining rigor and relevance. Through interactive models, data-driven investigations, and real-world applications, LabXchange supports educators in building their own confidence with these topics while helping students develop a deeper, more practical understanding of how data and AI shape the world around them.

How do you define data literacy?

Data literacy is the ability to read, interpret, analyze, and communicate information derived from data. It involves understanding how data is collected, recognizing patterns and limitations, and making informed decisions based on evidence. It’s not just about working with numbers, it’s about thinking critically about what the data represents and how it is used.

How does being data literate help learners beyond the classroom?

Data literacy equips students with skills they will use in everyday life, from evaluating news and social media claims to making personal and professional decisions. It helps them become more critical consumers of information and more effective problem-solvers. In a world increasingly driven by data, these skills are essential for informed citizenship and career readiness across virtually all fields.

As an educator, what role do you see AI playing in the future of education?

As a teacher of AP Biology, Honors Chemistry, and AP Capstone Research, I see AI as a tool that enhances learning rather than replaces it. It can support data analysis, modeling, and differentiated instruction, helping students engage more deeply with scientific concepts. At the same time, it makes it even more important to teach critical thinking, experimental design, and independent analysis, especially in research-based courses. Ultimately, AI will serve as a powerful learning tool, and my role is to guide students in using it responsibly while strengthening their ability to think critically and develop evidence-based reasoning skills.

‍

Stay tuned to learn more about LabXchange's AI & Data Literacy initiative! Explore existing data science resources in the LabXchange library.