Posted in: Aha! Blog > Eureka Math Blog > High-Quality Curriculum Mathematics data talks > Data Science: The Importance of Incorporating Data into Everyday Instruction
Every second, Google processes about 99,000 searches, which is a testament to the amount of data right at our fingertips (Flensted 2024). The amount of data in our world has increased exponentially over the last few decades and shows no signs of slowing down. From the job market to everyday life, our opportunities, decisions, and experiences are profoundly shaped by how we produce, consume, and interact with data.
It's clear that today’s students, starting at a young age, must be able to collect, organize, understand, and communicate data to meet the demands of modern society. From an employment perspective, the ability to use and apply data has become essential in many ways. According to the Bureau of Labor Statistics, occupations in data science and statistics will grow 35 percent and 32 percent, respectively, from 2022 to 2032 (“Occupations” 2023). And data literacy and data science have also become essential skills for jobs and innovation in nearly every sector of the economy, including tech, media, manufacturing, health care, agriculture, finance, education, and retail. From an individual and societal perspective, students need data literacy skills to navigate everyday decisions about their finances, political and social participation, health care, and more.
Unfortunately, research shows that student achievement in data literacy skills is declining. In a recent study, the Data Science for Everyone (DS4E) coalition examined student data literacy performance on the National Assessment of Educational Progress (NAEP) from 2011–2022. It comes as no surprise that the findings showed that the largest decreases in scores in Data Analysis, Statistics, and Probability happened during the pandemic. But this decline was part of a longer-term downward trend in outcomes that started well before COVID and was greatest for some historically underrepresented student groups, including Black and low-income students (Drozda 2023).
“Today’s fourth graders have the data literacy of third graders from a decade ago, and today’s eighth graders nearly have the data literacy of sixth graders from a decade ago. What’s more, this decline in data literacy is occurring at a faster rate than other math content areas in the NAEP assessment.”
(Drozda 2023)
Overall, from 2011–2022, data literacy scores dropped 10 points for grade 4 students and 17 points for grade 8 students. In terms of magnitude, the report explains, “Most experts believe 10 points is the equivalent of a single grade level, or a year’s worth of academic growth. Put differently, today’s fourth graders have the data literacy of third graders from a decade ago, and today’s eighth graders nearly have the data literacy of sixth graders from a decade ago. What’s more, this decline in data literacy is occurring at a faster rate than other math content areas in the NAEP assessment” (Drozda 2023).
Alongside students’ performance in data-related skills, it is equally concerning that students’ interest in math declines as they progress through the grade levels. The DS4E coalition also explored student attitudes toward math and found that 73 percent of grade 8 students agreed that “it is important to do well in math,” but just 58 percent of students in grade 12 did. Similarly, 40 percent of grade 8 students said that they are interested in what they learn in math, compared to just 31 percent of grade 12 students (Drozda 2023). The report ultimately says that these trends in students’ math interest “may be attributed to an outdated math curriculum that has not kept pace with the modern information age” (Drozda 2023).
Overcoming Barriers to Data Science Education
“…There is ‘lots of fear’ around data, and teachers are asking for help … Training for teachers is critical … Teachers come with a wide range of knowledge but sometimes lack the conceptual understanding of data science.”
(National Academies 2023, 31)
In 2022, the Board on Science Education at the National Academies of Sciences, Engineering, and Medicine held a workshop titled “Foundations of Data Science for Students in Grades K–12.” In a paper commissioned for the workshop, researchers examined the landscape of K–12 data science implementation, including barriers to implementing data science education. According to interviews with teachers across the country, these are some of the most common barriers:
- Confidence in data analysis, technology, or statistical thinking is persistently low among teachers.
- Standards or guidance for data science education and data ethics are inadequate.
- Instructional methods and technology that reflect the current world of data and computing are lacking.
- Data and statistics are often cut from courses or treated as secondary to other subjects (National Academies 2023).
The good news is that many schools, districts, and states have committed to increasing students’ experiences with data science. In 2019, only two states had data science programs, but that number had grown to 14 statewide programs in 2022 (National Academies 2023). Expanded access to data science across K–12 education is coming in a variety of forms, including “new standards, pilot course programs, and expanded pathways” (DS4E 2023).
But even amid this growing recognition of the need for more data science instruction, educators still face a lack of high-quality instructional materials that help them teach these important data literacy skills right now. One instructional resource that meets this immediate need is Data Talks—short activities that expose students to data and allow them to interpret data visualizations. A Data Talk offers students a data visualization, invites them to make observations and ask questions, and helps them to develop the critical-thinking skills they need to interpret the data surrounding them every day. Data Talks support students in becoming good analysts of data who interrogate both the data and the process by which it was collected.
The beauty of Data Talks is that they are short, flexible activities that do not require extensive teacher training or expertise to implement. They can provide students of all ages with exposure to many different types of data visualizations in a developmentally appropriate way.
Data Talks, and Great Minds Listened
Great Minds® makes knowledge accessible to all in the form of high-quality instructional materials, and data science is no exception. Great Minds has created a unique set of Data Talks in response to the growing number of states nationwide that now require that students have more experience interpreting and working with real data. The Mathematics Framework for California, for example, emphasizes the importance of student exposure to all types of data visualizations, including those that are not standard and those that include multiple variables. The Framework also calls for younger students to get exposure to data science in an introductory way.
These types of requirements motivated Great Minds to create a series of 120 Data Talks across grades K–9 that would meet the needs of educators and the demand for high-quality and user-friendly data science materials. The value in these Data Talks lies in their comprehensive and cohesive nature. The teacher–writers at Great Minds used their deep expertise in the field to source reliable data about engaging topics and to represent that data with fascinating, developmentally appropriate visualizations across grade levels.
Let’s look at some of the key features found in the entire series of Great Minds Data Talks.
- Knowledge Building: Great Minds Data Talks include a variety of visualizations that expose students to both familiar and unfamiliar data displays. The set includes traditional displays, like bar and line graphs, along with nonstandard data visualizations rarely found in mathematics textbooks. Combining this variety of data representations with real-world contexts allows students to build their data analysis skills while also building their knowledge of topics related to science, history, nutrition, popular culture, and more.
- Engaging: Real data and relevant contexts engage students’ curiosity and naturally spark knowledge-rich conversations. Great Minds Data Talks cover topics including sports, such as basketball players with the most missed shots and ice hockey championships; weather, such as the impact of wildfires and the movement of tornadoes; animals, such as wolves in Yellowstone and giraffe heights; space, such as trips to the moon and the earth’s orbit around the sun; and much more. The digital format of Data Talks ensures real, up-to-date data sets so that each exercise reflects data in the world around students.
- Coherent: Coherence is built within the series of Data Talks by using similar displays and topics across grade levels. Connections to Eureka Math2® concepts are indicated to teachers within the materials, and coherence across curricula allows these Data Talks to connect topically to Wit & Wisdom®, Geodes®, and PhD Science®. For example, certain Data Talks relate to the Wit & Wisdom and Geodes modules Powerful Forces, Creature Features, A Season of Change, and Good Eating. And connections to PhD Science include the modules on Survival, Weather and Climate, Energy, and Orbit and Rotation.
- Flexible: Each Data Talk is designed as a short, 10-minute activity that can be facilitated at any point during the instructional day, making them very flexible. The closing of a Data Talk isn’t a landing point, but rather a launch into other research, data, or even an entirely new investigation. This intentional design demonstrates to students how statistical investigations often end with a new beginning—with new questions and the need to learn more. The More page included with each Data Talk provides additional context and information about the Data Talk topic, and teachers can always extend the activity with the ideas presented in the More page.
- Accessible: Data Talks are low-floor, high-ceiling by design, which means all students can easily access the content, begin the exercise, and then participate at their own level as the exercise unfolds. Each Data Talk begins with a notice and wonder activity, followed by the consistent Understand, Apply, and Reflect routine. This routine helps students build habits of mind that will allow them to unpack any data visualization they come across. Data Talks are also created with the same high quality that characterizes all Great Minds curricula. All the data visualizations are designed with accessibility in mind, and each activity includes features like teacher notes, language support boxes, UDL suggestions, and opportunities for extension.
The Understand, Apply, Reflect Routine
This consistent instructional routine helps students build the cognitive skills they need to engage with any data visualization. Here is a sample of key questions that might be asked at each phase of the routine.
- Understand: What does this data visualization show? What information can you get from it? What else should you do to figure out this visualization (e.g., decode the key, define a data label, figure out what the title means)?
- Apply: Why might someone want to collect this data? What do they want to learn, and how are they hoping to use it? What story is this data visualization telling, and what story is left out? Where does the data come from? What biases do you see in it?
- Reflect: What do you want to know more about? What questions do you still have?
It has never been more urgent for students to become skilled users of data, which means we must equip teachers with the high-quality materials and guidance they need to build students’ data literacy. Together with teachers, we can use Data Talks to build classrooms with engaged students who have the data analytic knowledge and skills they need for academic success, personal and professional fulfillment, and thoughtful participation in our society.
For more information on Great Minds Data Talks, watch our free webinar, and check out our website for information on their full release for school year 2024–2025.
Sources
California Department of Education. 2023. Mathematics Framework for California Public Schools: Kindergarten Through Grade Twelve. Sacramento, CA: California Department of Education. Accessed March 6, 2023. https://www.cde.ca.gov/ci/ma/cf/.
Data Science for Everyone. 2023. “K–12 Implementation Models.” Accessed March 1, 2024. https://www.datascience4everyone.org/implement.
Drozda, Zarek. 2023. “Data Science Is Vital to Student Success. So Why Are Outcomes Going Down?” Data Science for Everyone. Accessed March 1, 2024. https://www.datascience4everyone.org/post/data-science-is-vital-to-student-success-so-why-are-outcomes-going-down.
Flensted, Torbjorn. 2024. “How Many People Use Google? Statistics & Facts (2024).” SEO.AI. Accessed March 1, 2024. https://seo.ai/blog/how-many-people-use-google#:~:text=Approximately%2099%2C000%20search%20queries%20are,people%20use%20Google%20each%20day.
National Academies of Sciences, Engineering, and Medicine. 2023. Foundations of Data Science for Students in Grades K–12: Proceedings of a Workshop. Washington, DC: The National Academies Press. https://doi.org/10.17226/26852.
U.S. Bureau of Labor and Statistics. “Occupations with the Most Growth.” Last modified September 6, 2023. https://www.bls.gov/emp/tables/occupations-most-job-growth.htm.
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Alyssa Buccella
Alyssa has nearly a decade of education research experience. She has led equity and student success research to support K-12 public school districts across the country in addressing their most pressing challenges, including college access, mental health, social emotional learning, and racial justice. Alyssa holds a B.A. in Psychology and Global Studies and an M.Ed. in Globalization and Educational Change from Lehigh University.