The Ultimate Guide to Data Literacy PD for Grades K to Pre-AP Educators
Data literacy PD is no longer optional—it’s essential. Yes, we know we are a bit biased on this one, but that doesn’t mean it isn’t true ;) Data literacy is a core competency for success in the 21st century. Workforce trends show it’s becoming essential across nearly every sector:
- 86% of organizational leaders say data literacy is essential for day-to-day work for their teams (DataCamp’s 2025 State of Data & AI Literacy Report).
- 46% of corporations currently provide data training (DataCamp’s 2025 State of Data & AI Literacy Report) up from 39% in 2022 (Moody, 2022, HR Dive).
- The demand is only growing — business leaders predict that by 2030, data literacy will rival basic computer skills in importance. (TDWI, 2022)
Despite the need and increase in trainings, workforce confidence in data literacy remains a challenge — earlier studies found that only about ~11% of employees felt fully confident in their data skills. (Qlik’s The Data Literacy Project, 2025). Therefore, building data literacy from kindergarten through high school graduation not only strengthens their problem-solving and critical thinking, but also prepares them for a data-rich future in which they can engage meaningfully with real-world issues and be ready for the workforce. Yet many teachers still haven’t received formal training on how to support data literacy across subject areas — especially outside of math.
As students grapple with interpreting graphs, analyzing trends, and building data-informed arguments across grade levels, educators need clarity, confidence, and the right tools to guide them. That’s why we wanted to share this ultimate guide to data literacy professional development(PD). We’ll walk you through what data literacy is, why it matters, and how schools can design training that actually sticks — equipping your teachers to build stronger, more confident learners.
Data Literacy PD: Why It’s Needed at Every Grade Level
And there is some good news! According to the State of Data Science Education 2025: Where We Are and Where We’re Going report (Data Science 4 Everyone, 2025, webinar recording here), more than 3,000 teachers participated in over 23,000 hours of professional development in data literacy and/or science education in the 2024-25 school year! Woohoo, that is fantastic. And there is a long way to go to support our roughly 3,000,000+ teachers nationwide ;)
Data literacy PD helps teachers understand not just how to use data themselves, but how to teach students to do things like:
- Ask thoughtful questions from and with data,
- Actively engage with and explore the data,
- Make claims supported by evidence,
- Identify bias or misleading representations, etc.
It is important to note that developing data literacy from elementary through high school is not just about teaching charts or graphs—it’s about building reasoning, critical thinking, as well as workforce (and adult) readiness skills for all students. Additionally the specific things we are asking students to do with data is way more than reading or making data visualizations. It encompasses things like:
- Asking questions & considering possible outcomes
- Generating or accessing data
- Quantifying data
- Organizing & processing data
- Visualizing & exploring data
- Adjusting data to reveal patterns (e.g., filter, simplify, or transform)
- Describing & analyzing patterns
- Interpreting data to learn something
- Articulating uncertainty
- Using or Building on new knowledge from the data
More on these aspects of working with data can be found in the Building Blocks for Data Literacy.
Yet, across the U.S., most students still lack solid, structured opportunities to build these skills. That’s why thoughtful PD for educators is so important: to help them bring data into their instruction in ways that empower all learners across all of our subject areas. So what could that look like?
Well for one we need to evolve key concepts across grade levels. Our students at all grades levels should be engaging with all of the above listed components of working with data. For example let’s consider how students progress in their "acknowledging attributes/variables” (a key part of quantifying data) from our youngest learners up in terms of what they do:
Grades K–2
- Describe different attributes of objects (or groups of objects) such as color, size, or shape.
- Decide whether an attribute is described by a word (e.g. color, shape) or by a number (e.g. how many).
Grades 3–5
- Identify categories, quantities, and ranges within an attribute.
- Recognize categorical attributes as those with discrete groupings (categories),
- Recognize quantitative attributes as those with numeric measures that have a range along a continuous scale.
Grades 6–8
- Understand attributes in the context of the dataset (e.g. what was measured or observed, how measurements were made, and possible reasons why they were measured).
- Consider how two attributes might relate to each other in the context of the dataset (e.g. one influences another, but not the other way around).
- Recognize a potential cause-and-effect relationship between stimulus (independent) and response (dependent) attributes.
Grades 9–12 (non-AP)
- Critique the attributes in terms of an investigation and/or broader context or problem (e.g., Are attributes sufficient? Relevant? Likely reliable?).
- Apply previous skills in combined or more complex ways.
Therefore all of our students within the K-12 system are working on progressing their skills around understanding what attributes/variables included in the data. But what it looks like in any given classroom differs across our grade levels. Thus no matter the level, teachers need PD that helps them scaffold their instruction to the grade level/band appropriate level of the data skills. We strongly believe also that the PD should help teachers respond to student misconceptions and connect data literacy to their existing curriculum.
What Should Data Literacy PD Include?
Whether you’re planning a single workshop or a full PD series, we have found there are a few key elements that make data literacy training meaningful and actionable for teachers:
1. Conceptual Understanding of Data
It’s not enough to show teachers how to plot graphs. Effective PD helps educators explore how students make sense of data. This includes:
- How students read and interpret graphs
- Common areas where misunderstandings arise
- How to teach analysis and reasoning, not just construction
By grounding PD in the why behind the data, teachers leave with a stronger sense of how to guide students’ thinking—beyond the mechanics.
2. Hands-On Instructional Practice
The best PD is experiential. For example in our in-school teacher training, educators participate in data tasks, analyze student work, and test strategies that align to their own classroom goals. The key is that teachers walk away not just with ideas, but with practice that they can immediately bring into their classrooms.
3. Cross-Disciplinary Integration
Data literacy isn’t just for math. It actively shows up in our science and social studies standards. It is critical to working with computer science and technology components. And it is required to make sense of many non-fictional texts we explore in English Language Arts…let alone how it shows up in other areas. Therefore, teachers benefit from learning how to make interdisciplinary connections across units/subject areas. And another critical, but often overlooked, aspect of this is norm setting on a few things:
- Who teaches what when in terms of students data literacy skills, and
- How we talk about different aspects of working with data with our disciplinary contexts…for example when do we use the same word and mean different things (e.g., patterns) or when do we use different words to mean the same things (e.g., increasing, ascending, positive, direct relationships).
This kind of integration helps students (and teachers) see data as a tool for thinking across subjects—not just a standalone skill.
4. Culturally Responsive and Equity-Centered Approaches
PD should help teachers explore whose data gets represented and how. This includes:
- Bringing in student, local, or global datasets that reflect the communities they serve
- Discussing how data can tell stories that either empower or marginalize
By centering equity, teachers can make data more relevant and inclusive for every learner.
5. Flexible Formats for Sustainable Growth
Data literacy PD works best when it’s ongoing, job-embedded, and meets the actual needs of teachers. Being flexible with the format is one key puzzle piece. Another we have found is iterative cycles of implementation and reflection. This cannot all be contained in a one-and-done session. It takes time for authentic and supported integration into and across our classrooms K-12.
Why In-School Training Is the Best Fit
Students who understand data are better prepared to:
- Think critically
- Participate meaningfully in civic life
- Engage with real-world issues
- Make informed decisions
- Be college and career ready
Delivering data literacy PD in-school makes it real and actionable:
- Relevance: Content connects directly to your curriculum and pacing
- Flexibility: Sessions can fit full days, half days, or planning periods
- Collaboration: Teachers work with peers and build internal capacity
- Impact: Strategies are applied immediately with real students
Teachers who receive strong PD are more confident, creative, and impactful—equipping students with skills they’ll carry far beyond the classroom.
Ready to bring data literacy to every classroom?
Explore our In-School Training Programs and schedule a Discovery Call to get started.
