Tuva for Science Education

Letting Students Lead: A Tenn. Science Teacher Navigates Curriculum Change

Middle school science in Collierville, Tennessee, looks a lot different this year.

Less time is spent taking notes, reading, and answering question sets, and more time is spent developing models, conducting investigations, and discussing findings. The change comes from a new 5E-based curriculum, in which students construct their own scientific explanations.

Teaching Through a Curriculum Transition

The shift is not limited to Collierville. Science educators across Tennessee are teaching through a major transition: a new curriculum aligned to updated state science standards.

By law, the Tennessee Board of Education is required to review core academic standards at least once every eight years. In late 2022, the board approved a revised edition of the Tennessee Academic Standards for Science that was developed to explicitly “integrate disciplinary core ideas with crosscutting concepts and science and engineering practices.” In other words, the standards are intended to help students not just memorize scientific facts but actively use evidence and reasoning to make sense of the world around them.

A list of state-approved curricula aligned with the revised standards was released in 2024, and districts began implementation at the start of this school year.

Navigating the Change

Collierville Schools, located in a suburb of Memphis, opted to use STEMscopes™ Science TN as the curriculum for their 6–8 science students. Leslie Austin, a 7th-grade teacher at West Collierville Middle School, is a fan of the 5E instructional approach used by the curriculum. She admits, however, that they were worried at first.

“Turning over the reins to the kids is a shift for a lot of people, and it can be really hard,” said Austin. “But it is really cool to see, if we give them the tools and access to the information, what they can discover.”

STEMscopes™ is one of six state-approved middle school science curricula. Each requires a similar shift: from consuming knowledge to actively building it.

Actively Making Sense of the World

A central feature of Austin’s classroom is a whiteboard coated with sticky notes. On each note is a student-generated question that links back to a real-world situation students are attempting to explain.

Austin’s driving question boards from semester 1 (left) and semester 2 (right). Austin has noticed an increase in both the number of questions and in “piggybacking”, or adding to each other’s questions.

As the unit progresses, students plan and conduct their own investigations and analyze others’ research to answer their own questions and, ultimately, construct an explanation of the phenomenon. Austin loves the “a-ha” moments when students make a discovery that connects to the question board.

“The kids get to answer those questions for their classmates. They start getting excited and wanting to know more. They are going to remember that more than me reading them something,” said Austin.

Data’s Role in Sensemaking

Data plays a crucial role in the student sensemaking process. Austin encourages her students to make claims using data from investigations they have conducted themselves or from a reliable study, but doesn’t permit them to just look up an explanation on their cell phone.

“AI can make up anything, but what backs it up? What makes it true? How do you know?”

“AI can make up anything, but what backs it up? What makes it true? How do you know this is the boiling point? How do you know the cell works this way? I want them to figure out the answers on their own.”

STEMscopes™, also recognizing data’s importance, bundled Tuva into their curriculum subscriptions for many schools. Tuva has since created a Tuva-STEMscopes™ Science TN Alignment Guide to make it easier for teachers to locate places where Tuva’s data-rich resources and graphing tools can be used to enhance the curriculum.

Tuva: Dual Learning Gains

“Where has this been all my life?”

That’s how Austin described her reaction after using “Boiling Water Wherever You Are“, an activity she found on the Tuva‑STEMscopes™ Science TN Alignment. The activity helped students grasp abstract concepts about how pressure affects boiling point using real-world data, while also embedding vocabulary and building transferable data literacy skills.

Students practiced identifying positive and negative relationships, experimenting with which variables to place on which axis, and choosing the best type of graph to represent their data. Visual learners could see patterns emerge, and kinesthetic learners engaged directly by manipulating the graphs and testing ideas themselves.

*Students can choose from multiple graph types in Tuva, allowing them to experiment with variables, axes, and visual patterns.*

For Austin, the most exciting part was seeing students take ownership of the data.

“It was something they had never done before—being able to choose what to put on the axes, change the colors, and see what patterns emerged. They could play around and see what they saw,” she said.

The Payoff

In Austin’s opinion, the new statewide approach does a much better job of engaging students and preparing them to ask questions, work with data, and defend their ideas.

Though the shift places new demands on teachers, Austin has noticed some advantages for them as well.

“It’s a lot of fun watching teachers like their jobs better.”

Teaching in Tennessee?

We’ve mapped Tuva resources to the Tennessee Academic Standards for Science. Search by grade level and standard here.

Teacher Helps Students Rethink Who Can Be a Scientist

As a teenager, Christine Adamson thought science was only for the few who could survive. “It felt like a weed-out type of class,” she recalls, “like it was supposed to be so hard that only a few people would be good at it.”

Now a science teacher at Day Middle School in Newton, Mass., Adamson is determined to change that narrative. “I want my students to walk away with this idea that a scientist can be anyone,” she says.

One way Adamson does that is through the Northeast U.S. Shelf Long-term Ecological Research (NES-LTER) Data Jam, a competition where students work with real ecological data and professional scientists.

Telling a Story About Data

This Data Jam challenges students to bring real data to life through creative storytelling. The word “data” might make some people’s eyes glaze over, but this project is anything but boring. Think crustacean costumes, video games, and illustrated storybooks.

All of the data comes from research conducted as part of the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Program. NES-LTER scientists collaborate to gather oceanographic data about the continental shelf over an extended period. To be eligible for National Science Foundation funding, LTER sites must include a broader impacts component.

Because K-12 students can’t easily join marine research trips, NES-LTER’s Education Coordinator Annette Brickley launched the Data Jam seven years ago. She selects teen-friendly datasets from recent studies and challenges students to tell a story using any expressive medium.

Tuva Helps Students Find The Story, Boosts Confidence

The first step of the competition is finding the story within the data. Adamson, like 90% of Data Jam participants, relies on Tuva for this phase.

Adamson recalled the first time Brickley showed her Tuva: “She’s showing us how she uploads the data. All of a sudden this graph populates, and you could just pull over the variables. This is amazing, right? And even the kids were like, ‘Wow!’”

The drag-and-drop interface helped students quickly make sense of the variables and the associations between them.

Adamson noted that Tuva also accomplished something deeper—it boosted students’ confidence. They were proud of the professional-looking visualizations they were able to create. For Adamson, that confidence is essential.

“I like having them feel successful in class,” she said. “So that if science is something they’re interested in, they feel like they can do science.”

In Adamson’s classroom, success breeds success and opens the door to students seeing themselves as scientists.

Real Data + Creative Outlet = Student Investment

Once students have used Tuva to identify interesting patterns or trends in the data, they unleash their creativity to tell the story. In past years, Adamson’s students have composed symphonies, developed elaborate board games, and recorded songs.

“The kids who are, during the year, maybe not as engaged— they just light up with this project,” said Adamson.

She quickly rattled off three examples: a group so engrossed in writing their rap about fish that they didn’t want to stop for lunch, a quiet student who found her voice narrating a group video, and a chronically absent student who started showing up every day during the project—and kept coming even after it ended.

But Adamson believes it’s not just the creativity that draws students in—it’s also the sense that they’re contributing to something larger.

“It’s not just a standalone lesson,” she said. “It’s connected to something real. They feel a lot more ownership over it than just doing regular classwork.”

NES-LTER scientists serve as judges, offering feedback to every group. For many students, this is a powerful moment: real scientists, from diverse backgrounds, are not only evaluating their work but engaging with it, showing that science is a community they can be part of.

That insight deepened after Adamson’s own experience aboard a research vessel, where she spoke with working NES-LTER scientists about what spurred them to pursue a career in science and how to interest more students.

The answer that stuck with her: show students how the data they’re working with might lead to real, positive impact. When students understand that their work matters—that it’s part of something bigger—they’re more likely to see themselves in the role of scientist.

This Year’s Contest

This year’s submissions are due in early June. While most participants are in Massachusetts and Rhode Island, the NES-LTER Data Jam is open to U.S. classrooms nationwide.

The official registration deadline has passed, but educators can still join by emailing Annette Brickley directly at abrickley.edu@gmail.com.

**Make Your Students into Data Storytellers!**

No matter where you are or what ecological concept you are studying, you can take a page from the Data Jam playbook. Find some real-world data, use Tuva to identify the story, then let your kids get creative in its telling.

Here’s how to find authentic data:

Find a classroom-ready dataset in Tuva’s Dataset Library. All of our datasets are generated from real-world data. (Some, like the Giant Kelp Growth dataset and Long Term Temperature and Precipitation, come directly from LTER sites.)
Upload data from an LTER study into Tuva. (Sign up for office hours if you need help.)
Upload data from governmental sources, such as NOAA, NASA, or Data.gov, into Tuva.

Youth Robotics Team Uses Data to Call for Change

A team of ten Massachusetts 12- and 13-year olds want community members in the Narraganset Bay Watershed to change their behavior.

Their advice? Apply phosphorous-free fertilizers, use plantings to filter water, and convert impervious surfaces to absorbent ones. All of these changes, they say, will help prevent harmful algal blooms (HABs) in the bay.

A multi-line graph shows how mean dissolved inorganic nitrogen (DIN) and dissolved inorganic phosphorous (DIP) changed throughout the months of the year. Both began to rise in May. DIP peaked in October at around 1.3 micrograms per liter. DIP peaked in December at just under 13 micrograms per liter.

The students reported, “Phosphorous, even in tiny amounts, can trigger HABs,”

The youngsters, who call themselves The Techno Tridents, are all members of a robotics team from Eastern Massachusetts. They became concerned about the nearby estuary this fall when they began preparing for the 2024-25 FIRST LEGO League Challenge. The annual challenge always includes two major parts: designing a robot and conducting a research project. The research portion requires teams to identify a problem related to the year’s theme, find out as much as possible about the problem, and work out an innovative solution. This year’s challenge theme was “submerged” and centered around oceanography.

The Techno Tridents quickly became intrigued by HABs, particularly an infamous Narragansett Bay bloom in 2003 that resulted in massive fish kills and shellfish recalls. The team wanted to know what brings about these blooms.

A “Huge Learning Curve”

The team’s coach, Pallavi Naravane, pointed the students toward the Northeast U.S. Shelf Long-Term Ecological Research (NES LTER) project. The NES LTER Schoolyard Program provides a series of datasets for use by middle and high school students.

The first dataset The Techno Tridents used. Explore it in Tuva.

The dataset most helpful for their inquiry was about nutrient levels in Narragansett Bay and comprised 1,229 datapoints. It was marked “advanced- HS recommended.” The columns across the top of the spreadsheet simply listed date, depth, NH₄, DIP, NO₃+ NO₂, NO₃, NO₂, and DIN. The problem? Many of the Techno Tridents had not yet completed a middle school chemistry unit let alone a high school chemistry class.

*Poster created by 8th-grader Akshita Serikar,*

To fully understand the data, the team needed to learn more about science concepts above their grade level such as the nitrogen cycle, the Periodic table, valency, ionization, pH, and eutrophication.

“There was a huge learning curve,” said Naravane. She laughed, admitting that, as an engineering teacher, she was included in that learning curve. “I just let them lead it,” she said.

Untangling the Data With Tuva

The students now faced the challenge of making sense of a complex, multivariate dataset. This is where Tuva became indispensable. The students uploaded the data provided by NES LTER into Tuva for analysis.

Naravane described Tuva as a “centerpiece” in helping her students uncover associations between variables. Using Tuva, students explored data analysis techniques. They learned how to add two variables on one axis, create dual-axis charts, and identify correlations. Tuva’s intuitive tools gave them insights that other software couldn’t match.

“Tuva labs is very sophisticated in the way that it allows you to see data,” Naravane said.

The story the data revealed was compelling: nutrient levels in Narragansett Bay spiked in October and November. Intrigued, the students sought to uncover the reasons behind this pattern.

The Techno Tridents included this graph in their project summary, writing, “The nitrogen and phosphorus spike in the fall… It is repetitive and we can see that the spikes are always more than 16uM of Nitrogen and 1.5uM of Phosphorus in October-November.“

To build a more complete picture, they explored additional attributes like temperature, rainfall, salinity, and occurrence of phytoplankton species. They discovered that October is when the water reaches its warmest temperatures and more rainfall occurs, contributing to increased runoff. This surge of nutrients, combined with peak temperatures, create ideal conditions for algal blooms.

Try using Tuva to look for relationships between sea surface temperature and phytoplankton.

Their analysis didn’t stop there. Using maps, the students noticed a high density of golf courses and lawns in the Narragansett Bay Watershed. Further research revealed that fall is a common time for lawn fertilization, adding another piece to the puzzle.

“We found a lot of these rabbit holes of science we could walk off into. And that’s exactly the kind of science learning I want,” Naravane said. “ You never get a chance to learn other things, unless you are powered by curiosity.”

Techno Tridents Secure Second Place With Data Analysis and Awareness Campaign

Based on all of the data, the students decided to launch a campaign to educate their community about responsible fertilization techniques. Their campaign included a variety of modes of communication: bookmarks with illustrations on one side and information on the reverse; an intricate, hand-drawn poster; and a Scratch animation.

Their data-backed campaign, along with their robot, helped the Techno Tridents land a second place finish in the Northborough FIRST LEGO League qualifier. Their work has also attracted the attention of other local organizations- including environmental non-profits looking to collaborate and a science-based art gallery that is going to display Serikar’s art (above).

Data’s Important Role in Innovation

Naravane coaches six teams via her small business Planet Robotics. Her work with students mainly centers around engineering. She is convinced that data needs to play a larger role in the engineering process.

“I really believe data is a new way to see things,” Naravane said. “If you don’t know what you are studying, how do you know it is a problem?”

Tuva Bolsters Multilingual Supports

Multilingual learners are the fastest-growing population of K-12 students in the U.S. Throughout the past six months, Tuva has taken a number of steps to ensure multilingual learners have access to rigorous STEM instruction.

1. Added a Keywords Feature

Academic language differs markedly from the language used in everyday social interactions. Fluency in conversational English doesn’t equate to academic fluency. That’s because social vocabulary is usually acquired within two years, whereas academic vocabulary can take up to 10.

To support students as they develop academic vocabulary, Tuva has added a keywords feature. When students click on an underlined keyword, a definition will appear. These definitions are written at a 6th-grade reading level.

Many of Tuva’s keywords are tier two vocabulary words.

Tuva’s keyword feature defines terms not frequently heard in everyday conversation. This includes tier two vocabulary, academic language used across multiple subject areas (e.g. clarify, analyze, compare), and tier three vocabular, disciplinary-specific terminology (e.g. photosynthesis, velocity).

Other keywords are tier three vocabulary.

2. Authored WIDA-Aligned Lessons

Using the WIDA framework, we’ve begun weaving multiple English language development supports into our math and science lessons.

Language Support Tips

All learners, but especially multilingual learners, benefit from explicit instruction in academic language usage. Our newest lessons include language support tips such as sentence starters, instruction on parts of speech, or lists of helpful phrases for using data to inform, explain, or argue.

This image is a screenshot of Tuva showing a language support box. It says, "You may see different word forms of correlate. Each on serves a different purpose in speech. Verb- correlate/correlates, noun- correlation, adjective- correlated."

Prompt Discourse
Conversation with peers helps multilingual students build a more nuanced understanding of STEM concepts. It also gives learners more opportunities to practice academic vocabulary and language.

We’ve made a concerted effort to promote discourse in any new full-length lessons and activities. By adding “Discussion” prompts to the lessons, we encourage students to discuss their thinking aloud.

Try One of Tuva’s New WIDA-Aligned Lessons

Elementary STEM: Preparing for a Hurricane

A map of North America. The states are green. A white, spiral-shaped cloud is above the southeastern portion of the United States.

Secondary Math: Tackling Correlations

Six American football players in a pile. Some wear golden helmets, others wear black helmets. They are tackling someone.

Secondary Science: Sun Seekers of Turtle Island

The picture shows a rock with a spiral carved into it. A beam of sunlight hits the spiral.

Check out our other lessons intentionally designed to support multilingual learners. View our secondary STEM lessons with ELD support or our elementary STEM lessons with ELD support.

3. Enabled Easy Language Translation

Translanguaging boosts STEM comprehension. It also accelerates English language development. Thus, Tuva has prioritized making it easy for users to switch between languages in our lessons. Simply click the three dots in the upper right of the instruction panel to make the Google Translate widget appear.

A screenshot of Tuva which shows the portion of the screen where the three dots can be found.

Do Kids Need to Learn to Graph by Hand?

Middle School Science Team Upends Expectations

Knowing how to create graphs by hand is an essential skill.

That may have been unexpected, coming as it does from the blog of a digital graphing tool. However, it’s important to clarify that using a graphing tool, like Tuva, and manually graphing are not at odds with each other; nor does one necessarily serve as a prerequisite. In fact, as the middle school science team at Northwest Middle School discovered, the two approaches are synergistic.

Northwest MS teachers Judith Neugebauer, Victoria Mauro, Anne Salisbury, and John Pikus.

“[Our students’] ability to see the numerical data in a graphical form is really transitioning from one realm to the other,” explained teacher Judith Neugebauer.

The team, which also includes teachers Victoria Mauro, Anne Salisbury, and John Pikus, is based out of a school in Salt Lake City. They began augmenting their manual graphing practices with Tuva’s digital graphing tools about a year ago.

The Most Persistent Problems for Novice Graph Creators

Adding digital graphing tools to the mix for novice graph makers is a step some are reticent to take. (Psst… I used to be amongst them.) Because digital graphing tools automatically do some of the steps for students, teachers wonder if students should know how to graph manually before they begin utilizing digital tools.

Before we address that concern, let’s take a step back to consider the most common skills with which novice graph makers struggle:

Placing variables on the correct axes
Setting up equal intervals and scaling them appropriately
Choosing an appropriate graph type
Accurately plotting data points
Including descriptive titles

The question is, then, will using digital graphing tools before students have mastered manual graphing prevent students from developing these important skills?

Better Together

Data literacy education expert, Molly Schauffler said that 15 years ago she would have said yes, but the development of drag-and-drop graphing tools, like Tuva, shifted her perspective.

“My sense now is that playing with the data and visualizing it on a digital platform gives students a visual sense of purpose, direction, possibility, and choice without getting mired in drawing and mechanics,”Schauffler said. “That said, I am still an advocate of hand drawing graphs alongside digital exploration.”

Schauffler is a founding member of a group called Partners in Data Literacy, a paleoecologist, an assistant research professor emerita for the University of Maine, and a former Tuva consultant.

“We still have them graph in their notebooks too, but this year it’s going way faster.”

The benefits of using both methods simultaneously are evident at Northwest, where teachers say making graphs on Tuva has hastened the development of manual graphing skills for their 7th- and 8th-grade students.

“We still have them graph in their notebooks too,” Neugebauer explained, “but this year it’s going way faster.”

The teachers there credit the uptick in pace to repeated exposure to and practice with variable placement and graph types in Tuva.

Our Suggestions for Achieving Synergy

Digital graphing tools exist on a spectrum from fully automated to completely open and incremental. When combining manual and digital graphing practices, consider how the features of the digital tool may impact skill development.

For Tuva users helping graphing novices master the five skills listed above, we suggest pairing manual graphing and Tuva in the following way:

Practice Manually	Practice With Tuva
Setting up equal intervals and scaling them appropriately	Placing variables on the correct axes
Accurately plotting points	Choosing an appropriate graph type
	Adding descriptive titles

In most instances, Tuva sets up intervals and plots data automatically once students have chosen which attributes (variables) to drag to which axes. Doing these things manually helps students understand a block on the graph represents a specific numerical increase.

That said, it is not necessary for students to practice establishing equal intervals and plotting data points every time they graph. In fact, sometimes it gets in the way of the other skills students are trying to master. Making graphs manually is so time-consuming that it is hard to achieve rapid repetition of a skill. Repetition is incredibly helpful for achieving mastery when it comes to placing variables, choosing graph types, and writing titles. Tuva enables targeted practice in these aspects of graphing. Students can also quickly and easily fix errors instead of needing to start all over, avoiding frustration and shutdown.

Swapped axes are a common woe of novice graphers.

Repeated practice can help.

Are We Graphing for Graphing’s Sake?

Perhaps, however, this entire discussion misses the point. Why is it important for our students to be able to create graphs? Is it simply so that they can create graphs? Of course not. The ultimate goal is to empower students to uncover insights about data through their graphs. Scientific literacy and data literacy are, after all, inextricable.

It’s easy to lose sight of that goal, however, in the day-to-day slog of asking kids over and over and over, “If you count up by ones, will you have enough space on your graph paper?” or, “Where does the independent variable go again?” And if we’ve lost sight of our goal, chances are our students never even knew a larger purpose existed in the first place. Of course, student motivation suffers when there is a lack of purpose.

Northwest teacher Anne Salisbury said Tuva has helped boost student engagement in the graphing process.

“I think using Tuva has convinced them that graphing has a purpose,” she said. “The point is not just to make a graph; it’s to use a graph. In the past we spent so much time getting them to physically graph on paper, that we did not have time to analyze data that is already graphed and figure out what it means.”