Building a Thinking Classroom with Data Science
January 16, 2025
Artificial intelligence has changed the landscape of education. There is now a shift in the role of teachers from the primary source of information to a facilitator of learning. In a world increasingly driven by data, one of the most critical skills we can teach our students is how to interpret and analyze data.
Data literacy – the ability to read, work with and communicate data – is essential for making informed decisions in everyday life. Data science uses a combined knowledge of mathematics, statistics, computer programming and artificial intelligence to make informed decisions. As educators, one of our most significant responsibilities is to prepare students to think critically about data in a world that relies heavily on informed decision-making.
In April 2024, the National Council of Teachers of Mathematics (NCTM) published a joint position statement with the National Science Teaching Association (NSTA), the American Statistical Association (ASA), the National Council for the Social Studies (NCSS) and the Computer Science Teachers Association (CSTA) about the importance of teaching data science to K-12 students.
“All subjects in school should recognize the contribution of data to their discipline and take curricular approaches that integrate data with disciplinary lessons where appropriate.” (NCTM, 2024)
We are in the digital age of data. From advertisements in social media feeds to weather forecasts, it is all driven by an invisible layer of math. Data is collected and analyzed, and that information is turned into insights. From sports statistics to climate change trends, political polls to spending habits, our students are surrounded by data that informs the decisions they make and the world they experience.
Students encounter data in countless forms, from graphs in news articles to algorithms in social media. Teaching them to analyze and question data prepares them to navigate this world. Working with data encourages students to ask questions, identify patterns and draw evidence-based conclusions. These skills are foundational to critical thinking.
This is where the concept of a “thinking classroom” comes into play. A thinking classroom prioritizes the development of students’ problem-solving abilities, fosters curiosity and encourages collaboration. It is an environment designed to engage students actively in the learning process. It’s a space where students are encouraged to think critically, ask questions and explore concepts beyond a surface-level understanding.
The framework for thinking classrooms stems from research-based strategies, such as Peter Liljedahl’s “Building Thinking Classrooms in Mathematics” model, which outlines specific practices that promote student engagement and autonomy in problem-solving.
Strategies to Build Thinking Data-Literate Classrooms
1. Incorporate Real-World Data: Present students with real-world data that requires deep thinking and multiple approaches. Use datasets that are relevant to students’ lives, such as local weather patterns, school sports statistics or trends in social media usage. Ask students to identify trends and predict future changes or outcomes.
2. Encourage Inquiry-Based Learning: Randomly assign students to work in small groups or pairs. Collaboration allows students to share diverse perspectives and develop a deeper understanding of concepts through discussion. Provide students with raw data and pose open-ended questions: What does this data tell us? What story might it be hiding?
3. Vertical Non-Permanent Surfaces (VNPS): Use whiteboards or similar surfaces around the classroom for students to work on. This promotes visibility of their thinking and encourages active participation.
4. Interdisciplinary Projects: Collaborate across subjects to use data in meaningful ways. For instance:
- In science, analyze environmental data to study ecosystems.
- In social studies, examine historical census data to understand demographic changes.
- In math, explore statistical concepts through real-world problems.
5. Focus on Data Ethics: Teach students to think critically about the ethical implications of data. Discuss issues like bias, privacy and how data can be misrepresented.
6. Questioning Culture: Foster a classroom culture where asking questions is valued as much as answering them. Encourage students to investigate further into the “why” and “how” of concepts.
7. Exploratory Environment: Create activities where students can experiment with data without fear of making mistakes. For instance, have them collect and analyze their own class data, analyze the results and present their findings.
Teaching students how to analyze and interpret data is not just a skill for the future; it is about empowering them to understand, navigate and shape the world today. By integrating data science activities into our lesson plans, we prepare students to think critically, solve complex problems and make informed decisions. As educators, let’s take on the challenge of transforming our classrooms into spaces where thinking thrives. After all, education isn’t just about passing on knowledge, it’s about inspiring minds to think, question and innovate.
This is the fifth in a series of guest blogs by the 2024-25 Michigan Regional Teachers of the Year. Sasha Wakefield is a mathematics teacher at Clio High School in Clio Area Schools.