View from the Classroom

HS Junior Melds Stats With Civics to Gain Insights into Infant Mortality

Data Crosses Disciplines, Yields Powerful Learning

Up until the mid-1800s, children had a 50% chance of dying before age 15. By 1950 the childhood mortality rate was closer to 25%. Today, it sits at 4.3% globally. Childhood mortality rates have experienced a steep, steady decline across the world.

So, when Kate Harrison, a high school junior in Charlotte, North Carolina, was sifting through data about infant mortality rates in different countries, Syria’s data gave her pause.

“Syria in particular has these two spikes, and I got really interested, thinking, what was happening at the time?” she said.

Thus was born a semester-long investigation.

Data Transcends Disciplinary Boundaries, Deepens Learning

Harrison was enrolled in an honors statistics class at Fusion Academy where she’d been charged with undertaking an interdisciplinary project. She’d decided to apply statistics to explore history, but identifying a focus took time.

Her original idea was a bit nebulous, but it centered around trends in warfare over time. To clarify her question, she began exploring data. In the process, she stumbled upon the Syrian infant mortality data. That’s when nuanced and intriguing questions pushed their way to the forefront.

Harrison immediately noted an association between the timing of armed conflicts in Syria and the spikes in infant deaths. She noticed that after the start of the Islamist uprising in Syria in 1981, infant mortality increased by 4.24%. The nation suffered an even more drastic 52.7% increase in the infant mortality rate from 2010-2014 at the beginning of the Syrian Civil War.

Harrison discovered that in both instances there had been a concurrent rise in overall mortality. However, she knew that infants didn’t fight in the wars, so what were the underlying connections? Harris worked with her faculty advisors, social studies teacher Rick Fera and statistics teacher Chad Boger, to brainstorm variables that may have influenced infant mortality.

Variables she explored included birth rates, governmental regimes, international aid, gross domestic product, basic sanitation, basic healthcare access, and vaccination rates. She compiled data about these factors from Our World in Data and the World Health Organization and imported it into Tuva for analysis. Harrison said identifying changes and interpreting patterns was easier for her when she used Tuva.

“You really just can’t tell using a table because there’s so many numbers and so many different data points,” she said. “And so getting to put that all into one tool and really visualize it without having to go through the hassle of actually plotting out each point, and probably doing something wrong, was very helpful.”

Surprises in the Data

In some cases, Harrison was surprised at the lack of correlation between variables. She had assumed, for example, that GDP would have a large impact on infant mortality rates, but the data did not show a correlation. In fact, Syria experienced a financial crisis a few years before the civil war, but the infant death rate did not experience a resultant increase.

What did show a correlation with infant mortality – vaccination rates. In the early 1980s, Syria engaged in a national immunization campaign, and infant mortality rates showed a steep decline. However, when immunization rates faltered during the civil war and uprising, infant mortality spiked again.

Using Data to Inform Priorities in War-Torn Nations

“This data suggests that immunization programs and keeping healthcare systems intact should be a high priority in war-torn nations,” Harrison concluded. “Several relief programs are focusing on integrated management of childhood illnesses, which includes improving case management strategies of healthcare providers, healthcare systems, and families.”

Boger, Harrison’s teacher, applauded her work, saying she’d exceeded his high expectations. This spring, Harrison will have another chance to explore her passions with a civics math class she’s enrolled in.

“I personally see data as the backbone of any social change.”

She is also beginning to think about life after high school. She’s begun exploring four-year colleges and aspires to pursue degrees in political and environmental sciences.

“I personally see data as the backbone of any social change,” said Harrison. “Being able to visualize and look at data clearly is essential to taking meaningful action and maximizing your impact. I see this, especially with environmental justice and climate change. Data will help determine which areas are most in need of relief and which areas will face the most impact. I hope to be able to focus on data-driven environmental policy work in the future.”

Inspired? Explore Data You’re Passionate About

Find data that sparks your curiosity.
Click “Upload Dataset” from your Tuva dashboard or type tuvalabs.com/upload in your web browser’s URL bar.

3. You may now import a dataset from your computer, Google Drive, or One Drive, or by dragging and dropping your CSV, XLS, or XLSX file into the gray rectangle.

4. You’ll be prompted to review your data. Afterward, you’ll be taken to a visualization screen where you can begin analyzing your data.

For more detailed information and instructions, visit our Support Page: Uploading Data into Tuva. Also, we’d love to see the data visualizations you create! Share it with us at jocelyn@tuvalabs.com.

Math Teacher Delivers Personalized Learning at Scale

Math teacher Chad Boger prepares 30 different lesson plans per week. Increasingly, he’s using Tuva to make that formidable feat more manageable.

Boger is a teacher at Fusion Academy, a private school that offers one-on-one, personalized learning. The school serves students who thrive in a non-traditional setting. Fusion Academy promotes its program as specifically advantageous for twice-exceptional students and neurodivergent students, such as those with ADD, ADHD, or anxiety.

Boger said he enjoys working with kids at Fusion because he “gravitates” toward kids with special learning needs. He added that the one-on-one nature of his work is a boon because he gets to know each student well.

The Challenges of Condensed Class Time

That said, the one-to-one approach presents unique challenges for instructors. In a typical high school course, a student is in the classroom with their teacher for an average of 3 hours and 45 minutes per week. Fusion Academy teachers, in contrast, get just two 50-minute sessions.

Because instruction is condensed, they must be efficient with their face-to-face time. Boger is always looking for resources to help him optimize instruction time. After stumbling across Tuva this fall, Boger has used it frequently.

“Tuva is super intuitive, and it is going to save me so much time,” he said

This year, Boger’s caseload is primarily composed of juniors and seniors learning statistics. He found that teaching students to use spreadsheets was inefficient.

“It felt like a lot of wasted time when the goal was data analysis,” he explained.

This fall most of his pupils are working on descriptive statistics. Boger appreciates how easy it is to examine qualitative and quantitative data in Tuva. With the click of a few buttons, students can quickly separate the data into categories, make a box plot or histogram, and compare the spread and median of each category of data.

“Doing the same tasks with a spreadsheet,” he noted, “would have taken so much longer.”

Boger’s students use Tuva to efficiently make data displays like this one.

Never the Same Lesson Twice

Fusion Academy is not just one-to-one; it’s also personalized. Personalized learning is an approach whereby student interests and learning styles guide content and approach.

“We know that every child learns differently,” Boger said. “In a mentorship/teacher relationship, you can learn about each student’s preferences and tailor your lessons and instruction style to your learner’s needs.”

“We know that every child learns differently.”

A preliminary study by RAND Education and the Bill and Melinda Gates Foundation suggests personalized learning can help improve outcomes for a broad range of students¹. But it’s a heavy lift for educators. Unlike in a traditional classroom, instructors cannot plan a lesson and reuse it for all of the other sections of that course. Each lesson must cater to the unique interests and needs of the student. But how do you do that when you are planning 30 lessons a week?

Boger personalizes his statistics course by allowing students to select a topic they’re interested in and find a related dataset. Interests have ranged widely- from music to nutrition and book genres to Supreme Court data. Regardless of their chosen data, Boger has students upload it into Tuva for easy exploration.

Last semester, Boger uploaded the dataset that was used to make this visualization about crime rates. Users can upload up to five datasets to Tuva for free. Try it!

Passionate About Data Literacy

Teaching statistics is Boger’s job, but that’s not all it is. It’s also his mission. Boger believes that by getting kids invested in learning statistics, he is preparing them with the data literacy skills they need to thrive in the information age.

“If I can at least expose them to these things and help them think more critically—is it coming from a reliable source? Is it someone trying to push their agenda? That’s what I am trying to get across—not just can you calculate a formula.”

Pane, John F., Elizabeth D. Steiner, Matthew D. Baird, Laura S. Hamilton, and Joseph D. Pane, How Does Personalized Learning Affect Student Achievement? Santa Monica, CA: RAND Corporation, 2017. https://www.rand.org/pubs/research_briefs/RB9994.html. ↩︎

This Teacher Wishes Her Content Wasn’t Relevant

The Unique Challenges of Teaching About Environmental Injustice to Students Who Are Living It

Satina Ciandro’s environmental science students have experienced environmental injustice firsthand, which, paradoxically, makes it harder to teach about climate change.

On the one hand, it’s personal- offering baked-in relevance. On the other hand… it’s personal. Which means it’s also emotionally fraught.

“It took me 23 years of teaching science to really teach about climate change. Not just mention it, really teach it,” admitted Ciandro.

A Student Body Familiar with Inequity

Ciandro teaches science at Watsonville High School, located in a small city in the Monterey Bay Area of California. 96% of her students are Hispanic. 88% of her students are economically disadvantaged.

“Most of my students are students of color and they understand injustice very well,” said Ciandro.

In fact, many of her students were directly impacted last March when the Pajaro River Levee was breached, flooding homes in a low-income community primarily inhabited by migrant workers and their families. Needed repairs on the levee had been deferred by the Army Corps of Engineers when their cost-benefit analysis concluded the low home values in the area didn’t warrant prioritizing levee repairs.

Getting Past the Paralysis

The breach is just one example of environmental injustice Ciandro’s students have faced. A 2021 Environmental Protection Agency study indicated, “…the most severe harms from climate change fall disproportionately upon underserved communities who are least able to prepare for, and recover from, heat waves, poor air quality, flooding, and other impacts.” Racial and ethnic minority communities are particularly vulnerable, they stated.

Ciandro’s hesitancy to really go deeply into climate change stemmed in part from recognition that discussing yet another example of environmental injustice would be triggering for her students. She worried her lessons would be all doom and gloom.

Ciandro also worried about her lack of perspective. How could she teach about an experience she had not had?

“I am a white lady… I don’t know what they are living through,” she said.

Getting it right felt insurmountable.

Over the past few years, Satina has picked up a few trauma-informed strategies that help her feel more comfortable delving into the science of climate change and all of its messy ramifications. She’s learned that providing time and space for students to process things that are emotionally triggering is imperative. Ciandro incorporates art, journaling, and other forms of reflection into her science instruction.

She’s also learned that focusing on solutions helps reduce the doom and gloom factor.

“You can’t just point out the injustice and not do anything about it,” Ciandro said.

A recent study revealed 59% of young people ages 16-25 were “very” or “extremely” worried about climate change, a phenomenon increasingly known as eco-anxiety. Some eco-anxiety can spur people to action; too much eco-anxiety can have the opposite effect, leading to despair and inaction.

Having students take steps to help solve the problem can be empowering and can reduce anxiety. She cautioned, however, that you need to explore solutions in a way that does not put all the burden on the students to figure it out.

“That’s the point of the whole lesson- not to make you feel bad, but to consider what are the solutions, and how are we going to do the things to fix it?”

Striking the Balance with Urban Heat Islands

Recently, Ciandro applied these trauma-informed strategies in an urban heat islands unit. Ciandro was inspired to take this angle by Dr. Tammie Visintainer when she participated in her National Science Foundation-funded Climate Justice Action Research Summer Program at San Jose State University. The cohort of participating educators are all using urban heat islands as a lens to investigate climate justice with their students.

Urban centers tend to be hotter than surrounding rural areas. Materials like brick and pavement absorb and hold onto more heat than vegetation. This creates “islands” of heat. As the climate changes, heat-related deaths have also increased. Heat-related deaths in the United States spiked 59% between 2018 and 2022 according to the National Center for Health Statistics. People in cities are at higher risk of heat-related ailments.

Ciandro knew from her program that even within the cities, however, the effects of heat are not felt equally. Urban areas with fewer trees get hotter. Urban areas with lower tree density usually have two other things in common: high minority populations and historical subjection to redlining. Redlining was a practice carried out by lenders to create policies around who they would lend money to.

Certain districts were “redlined”. Mortgage lenders marked them in red on the maps, which meant they were coded as “hazardous.” Banks would not give mortgages to people buying homes in redlined districts. The rationale listed for assigning a specific neighborhood rating often cited race.

In nearby San Jose, California, for example, agents specifically noted one of these two reasons: “inharmonious racial concentration” or “heterogeneous” for five of 12 districts rated “hazardous.”

“When I went through history class in my white suburban school, I never learned about redlining. I did not know that it was on purpose and that it was systemic. I didn’t know. I know it’s not an excuse, but I’m learning with them,” said Ciandro.

Ciandro wants to make sure her students do learn about redlining. She designed a two-month long, project-based unit around the urban heat island phenomenon. Within the course of her unit, she wanted her students to discover the temperature differences; do some experiments to determine what factors affect temperature in our built environment; uncover the correlation between the 1930s neighborhood ratings and heat; and to take action to make a change.

How Tuva was Able to Help

Ciandro found that premade graphic visualizations about urban heat islands are easy to find, but she wanted students to be able to explore and manipulate the raw data themselves. Discovering a relationship on your own as you tinker with data makes a bigger impression than observing it on a premade graph. Ciandro’s go-to program for data exploration is Tuva. Ciandro has been a loyal Tuva user for many years and uses at least one Tuva activity per unit in her environmental science course.

Ciandro immediately went to Tuva in search of a relevant dataset but was disappointed to find we did not have one. After a conversation with us this summer during which she expressed a need for a dataset about urban heat islands and redlining, Tuva team member Annette Brickley curated one. She located a 2020 research paper by Hoffman, Shandas and Pendleton from Groundwork USA. When Brickley reached out to ask for permission to use the data on Tuva, Hoffman generously shared their complete dataset. Tuva’s dataset pulls out data from seven of the U.S. cities included in Hoffman’s paper.

Later, Ciandro used Tuva’s Activity Builder to create a lesson that would help her students explore the dataset and discover relationships between neighborhood grade, tree canopy, impervious surfaces and temperature. The story the data tells is pretty bleak, but Ciandro manages to infuse hope at the end of the activity.

Box plot showing that neighborhoods given ratings of C and D in the 1930s are hotter today than those that were rated A or B.

“Imagine you are a city planner and your job is to allocate funds for a major climate action grant,” she writes. “How will you distribute the funds to each type of neighborhood? Justify your answer using data.”(We liked her activity so much, we published it. Access it here.)

Ciandro’s students also collected data across the Watsonville High School campus. Each group selected two spots, collected surface temperature data once per week, and entered the data on Tuva. Through this exercise, they observed locations near concrete were consistently hotter than green spaces.

Student Empowerment

As the unit neared its end, four of Ciandro’s students – Jazmyn, Mario, Rocio and Anail- gathered around a Zoom meeting to tell me about their learning experience.

“I did not realize how impacted our little city is because it is so based on concrete,” noted Anail. “My (part of the) city is in the red line,” she added.

The other students agreed with Anail that the last few months have been eye-opening. Until this unit, they did not know urban heat islands existed let alone that extreme heat is worst in areas that were historically redlined. The other thing they agreed on was that everyone else in Watsonville should be made aware of the problem too. Jazmyn laid out her hopes for her community.

“I want them to get a better idea of how it actually affects us in our daily lives, I want them to not feel negative because there are solutions to it, and I want them to come together as a community to plant more trees,” she said.

As a culminating project, student teams created podcasts to help educate their community. The podcasts, which they plan to submit to the KQED Youth Media Challenge, played the dual role of helping students process injustice and giving them a way to fight back against it. (Want a sneak peek before they’re live? Listen to Jazmyn and Mario’s submission here.)

Teaching Tough Topics: “Something We Need”

Ciandro says teaching tough topics helped her grow as a teacher.

“It helped me as an educator to teach something that is tough to teach. It is a different way of teaching, and it’s something we really need,” said Ciandro.“You have to do your best and hope you are going to do more good than harm.”

Data Visualizations Make the Invisible Visible for Hands-on Learners

A strand of human DNA is a mere 2.5 nanometers wide. To put that in perspective, a sheet of printer paper is 100,000 nanometers thick. It’s no wonder high school microscopes are not powerful enough to enable students to view DNA! That poses a challenge for high school biology teachers, though. Anything at such an infinitesimal scale is abstract. It’s quite the trick to teach about how structure relates to function for something none of the students have ever seen.

High school science teacher Catia Wolff recognizes the need to make genetics more concrete for her students. This is especially true because of the population of students in her classes.

“Our school attracts students that prefer working on hands-on projects rather than a traditional setting,” explained Wolff.

Wolff teaches at the Rockland BOCES Hudson Valley Pathways in Technology Early College High School, more commonly referred to as Hudson Valley P-TECH. The program is part of the larger New York State P-TECH Program initiated a decade ago with dual goals of preparing students for high-skill, high-wage STEM jobs and ensuring employers have access to a talented and skilled workforce. Students who complete the program at Hudson Valley P-TECH graduate with both a high school diploma and an associates degree at Rockland Community College. The school tends to draw students with a talent for and affinity toward working with their hands.

Hudson Valley P-TECH attracts students who are hands-on learners.

Wolff carefully selects and sequences lessons to make genetics more tangible. Her process starts with three-dimensional modeling. She gives her students a DNA sequence. Students create a complementary DNA strand. Then they model the processes of transcription and translation, simulating how a cell carries out protein synthesis.

After completing this process, Wolff found her students were still struggling to understand how all the cells in our body can have such drastically different characteristics while housing identical DNA. They didn’t understand what gene expression means. They needed something more. What Wolff did next did not surprise P-TECH Guidance Counselor Allison Paul.

“Tuva caught my eye right away. Students can see it, they can manipulate it. They can do it. They’ll say, ‘Look what I made!’”

“She is always learning. When most teachers just want to take the summer off, she is taking a course. She is constantly learning and constantly trying to improve,” said Paul.

Instead of adding in a lecture, reading or video, Wolff began searching for resources that would cater to her students’ learning style. What she found was Tuva’s activity Genes: To Express or not to Express? That is the Question.

The activity uses a dataset curated from The Human Protein Atlas, a Swedish-based program with the aim to map all the human proteins in cells, tissues, and organs. Tuva’s dataset includes 35 different genes, the function of the proteins they code for, and whether or not those genes are expressed in the tissues that make up the eye, skeletal muscle, stomach and tongue. During the activity, students look for patterns of gene expression and hypothesize an explanation of the results.

“They had to figure out the puzzle. It made them really think. It really sparked conversation,” said Wolff

This dot plot shows the genes expressed in two different tissues: skeletal muscle and stomach. It has tissue type on the x-axis and gene name on the y-axis. The legend shows the function of the proteins created by the genes. Students can see that four genes are expressed in skeletal muscle that are not expressed in stomach tissues.

Throughout the course of the activity, students use Tuva’s drag and drop graphing tools to create visuals that help them compare the tissues and puzzle out why some tissues express certain genes while others do not. Wolf observed that having a model, a graph that students could actually see and manipulate, helped them comprehend how DNA connects to cell function.

“Tuva caught my eye right away,” Wolff explained. “Students can see it, they can manipulate it. They can do it. They’ll say, ‘Look what I made!’”

Reforging Human Connection Post-Pandemic… With Data

Schools across the nation report student behavior, engagement and academic performance have all dipped below pre-pandemic levels. In fact, one Stanford University study found that chronic absenteeism has doubled, jumping from 15% in the 2018-19 school year to 30% in the 2021-2022 school year. The reasons for this decline are complex and much-debated. Regardless of the cause, as educators, what do we do to motivate students?

“What I find works the best is you getting to know who they are and them getting to know who you are. Then they start wanting to do better,” said Doug Page, a veteran algebra one and AP statistics teacher at the Galileo Academy of Science and Technology in San Francisco. “It takes a while,” he admitted.

Page’s approach is not a new one. In 1985 psychologists Richard Ryan and Edward Deci introduced the Self-Determination Theory of motivation. Their research found that relatedness, autonomy and competence are three major drivers of human motivation. Their findings challenged Skinnerian behaviorism and changed the way educators approached student engagement. Less carrot/stick, more connection.

A Clever Way to Get Acquainted

Page has found a creative way to get to know students while simultaneously introducing them to some basic statistics- collecting data. During the first few days of his AP Statistics class Page disseminates a Google survey. Students answer a variety of questions about themselves. (Try it out here.)

Some of the questions are demographic in nature. How far do you travel to get to school each day? How many siblings do you have? Other questions focus on personal habits and preferences. Do you use social media? How many texts did you send yesterday? What sports do you play?

Page opens the data in a Google spreadsheet, removes student names so the data is anonymous and uploads the data to Tuva. He shares the data with his students via Tuva. Then, students can quickly ask and investigate questions about their class. In this way, Page gets to know his students, acquaints them with Tuva’s graphing tools, and introduces some foundational statistics concepts.

Unfiltered graph showing correlation between texts sent and texts received.

Filtered graph showing a correlation between texts sent and texts received.

Page used texting data from the student survey to teach about linear regression. Tuva’s simple filter tool enabled him to easily demonstrate how outliers can skew the data.

Page continues to use Tuva for a variety of assignments throughout the year.

“Sometimes I want to spend the time analyzing the data, not doing all the mechanics. The mechanics are a time sink. What I love about Tuva is that it is so drag and drop. You can do so many things so quickly.”

The Bigger Picture

Not only has Tuva enabled Page to connect with his students, it has also helped him harness data about school wide indicators of student engagement, such as tardiness and absenteeism, and use it to problem solve. For example, when Page noticed high levels of tardiness during first period classes, he began to collect data. He uploaded the data into Tuva, shared it with colleagues, and launched a productive conversation about how to improve first period attendance.

Teaching is a hard profession, but it’s never a dull one.

“Students always say, ‘Isn’t it boring teaching the same thing for 25 years?’” Page said. “But while the material stays the same, the people change. I tell them, it’s not you sitting in the same seat everyday.”

Page said it is these ever-changing personalities and the opportunity to connect to each kid and find out what motivates them that keeps him going.

Want to Try It?

After you make a getting to know you survey using Google Forms, it’s easy to import your own data into Tuva from the Google Spreadsheet it generates. Visit Tuva’s support section or click this link to learn simple steps for uploading your data in Tuva.