The Data Literacy Company

Building for a data literate future. Making data exploration, analysis, visualization, and interpretation accessible to all.

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Tuva in an EdTech Research Session at the New Schools Summit

Tuva is excited to participate in a session alongside WestEd and NSVF Ignite on EdTech Research that Empowers Educators and Entrepreneurs at the New Schools Summit in San Francisco on May 11, 2016.  

Other participant teams in this session include: Distinctive Schools, Rocketship Education, Lexia Learning, Proving Ground Project at Harvard Center for Education Policy Research, and MIND Research Institute. 

It promises to be a fantastic session, exploring the paramount topic of how rigorous education research can inform the design and development of tools and products to drive more effective teaching and learning in the classroom. 

Are you planning to be at the New Schools Summit? If yes, please join us at the session. 

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Explorar datos en Tuva

Tuva’s dynamic, easy-to-use data exploration and visualization tools are now available in Spanish.

Today, we are excited to take our first few steps in bringing Tuva’s Data Literacy Solutions to schools, higher education institutions, businesses, and sustainable development organizations globally. 

Our dynamic, easy-to-use data exploration and visualization tools are now available in Spanish, enabling Spanish-speaking learners around the world build a strong foundation in data and statistical literacy.

You can find our Spanish language datasets on our Tuva Datasets Library.  

Once you choose your Spanish-language dataset, you will find that all the dataset attributes, as well as all the features and functions on the toolbar are labeled in Spanish. 

Over the next couple of weeks, we will make Tuva’s data exploration and visualization tools available in other languages, so please stay tuned for further updates and announcements. 

For now, vamos a aprender datos sobre Tuva!

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Graph Choice Chart

This blog post is written by Molly Schauffler. Dr. Schauffler is an Assistant Research Professor at the University of Maine School of Earth and Climate Sciences.

So, your students have some data. Now what?

One teaching challenge is how to guide students to apply math skills when they “analyze and interpret” data in the context of learning content in other subjects -- science, or history, or social science. 

Many educators see students stumbling to apply basic data literacy skills such as organizing data, graphing, fitting lines and thinking statistically in general, when working outside of math class with real (often “messy”) data about the real world.

In our work in the Maine Data Literacy Project over the last six years, we observed, over and over again, three glaring weak spots in students’ data literacy:

Lack of a clearly-stated driving question or claim to investigate

Overwhelming tendency to plot data in bar graphs as a default graph choice.

Absence of discussion about variability in data.

We wondered: how could we help students frame clear, statistical questions to drive their inquiry? How could we help them make reasoned decisions about how to visualize data as evidence? How could we help them begin to see, describe, and make sense of variability in data?

And so, the Graph Choice Chart was born. The Graph Choice Chart (GCC) proposes five types of questions that students are likely to investigate:

Questions about variability within a group

Questions about comparing groups

Questions about Correlations

Questions about change through time (a special kind of correlation)

Questions about how a group is proportioned into sub-groups.

                                       Screenshot of the Graph Choice Chart 

Students are prompted to clearly state (write out!) a complete question in one of these forms, and then to follow a decision tree for choosing -- based on the nature of their question --  what kind graph would make sense to use for developing their evidence.  

In addition to helping students clarify the purpose of their analysis, the GCC maps a framework for building statistical thinking and language, informally at first.  

Students make deliberate decisions within the framework about what kind of question to ask, what kind of data are needed (categorical or quantitative), and what kind of graph makes sense for visualizing evidence. 

It prompts them to adopt language for visualizing and describing variability in data, an underpinning of reasoning about data. Once they master these skills, they are ready to move beyond the GCC to more complex kinds of questions and more quantitative analyses.

Tuva is a perfect environment for putting the Graph Choice Chart to work, whether students are collecting their own data, or working with Tuva Datasets. 

In future blogs, we’ll talk more about how early informal focus on variability supports the Common Core Math Standards and is a key underpinning to data literacy.

Download the Graph Choice Chart by logging into your Tuva Dashboard or the Tuva Resources section, and share it with your students and colleagues today. 

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Introducing Data Literacy 101 course on Tuva

This blog post is written by Molly Schauffler. Dr. Schauffler is an Assistant Research Professor at the University of Maine School of Earth and Climate Sciences. 

Raise your hand if the idea of teaching your students data analysis and statistical thinking is a little unsettling for you.

For many of us who teach social studies, history, language arts, and (yes) even science, it has been a very long time since we took a course in statistics. For many, statistics is a scary label.

Even fewer of us have ever had training in how to incorporate statistical thinking into curriculum for young students. Yet assessments and standards expect our students to analyze and interpret data and make compelling arguments from evidence. Yikes.

The good news is that statistics educators and education researchers, and Tuva, promote an initial exploratory approach to learning how to think statistically about data. Research finds that students have lots to say about data once they have tools, opportunity, and guidance to explore data informally and reason about the stories they find.

Quantitative, or “Confirmatory” statistical analysis comes later, once students grasp challenges of making informal inferences about groups and attributes that are variable. 

In Exploratory Data Analysis, students first learn to recognize and talk about variability, and how variability and certainty are related. They learn to explore data, make informal claims, and develop language for describing their data.

If you feel hesitant about guiding students in data analysis, you are not alone. Many of you have asked for some kind of “orientation” for students starting out with data on Tuva. 

Today, we are excited to launch Data Literacy 101, a course with modules and lessons designed to establish fundamental exploratory data analysis skills (“Level I”).  

In the coming weeks, we will add lessons that scaffold students in more quantitative analyses (“Level II”), that then launch them into a grounded and integrated approach to analyzing data as evidence (“Level III”).

Data Literacy 101 lessons incorporate pre- and post-assessment questions to help identify gaps and gains in learning. Lessons are tagged to identify relevant data literacy standards. Follow-on activities will give students practice in skills just learned in a lesson using datasets tagged by content area. 

In addition to building students’ skills, Data Literacy 101 is a useful reference if you want to refresh your own familiarity with basic statistical concepts and tools and language.  

Data Literacy 101 can help you and your students experience the fun of playing with data and telling the stories they find. Let’s get started! 

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More Updates to the Filter Bar

We have made additional updates to the Filter Bar on Tuva Datasets, following up from our announcement a few weeks ago regarding a more powerful Filter Bar. 

Now, you can filter for Tuva Datasets and activities by a specific Common Core Math Standard, Domain, or Topic.

The CCSS-related Filter categories include: Comparing Groups, Correlation, Comparing Data, Linear Equations, Modeling, Quantitative Relationships, and many topics and standards.

In addition, we are continuing to extend our coverage of the Next Generation Science Standards, and have curated a number of fantastic new datasets covering additional NGSS Physical Science, Life Science, and Earth & Space Science standards. To learn more, explore all the datasets in our Tuva Datasets Library. 

Remember, you can always reach out to us if you are unable to find a dataset for your needs. 

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Coming Soon - Automatic Grading on Tuva!

During the initial design phase of Tuva Activities and Lessons, one critical decision we made was that activities on Tuva would only initially support one item type – open-ended questions.

Why? We felt that activities and lessons based on authentic datasets gave both educators and learners a unique opportunity to look beyond the straightforward multiple-choice and True/False questions. 

With actual data and tools at our fingertips,  educators can pose a number of interesting, open-ended questions that gave learners an opportunity to:

Practice and gain exposure to the language of data, statistics, and graphing.

Construct arguments and support their reasoning with evidence from the data and their own visuals.

Explain their thinking in words, giving them an opportunity to focus on their grammar, sentence construction, as well as learn the techniques of quantitative reasoning.

Describe in words the various aspects of the data, including:

Any patterns or interesting phenomenon they discover.

Distribution of various attributes, such as its shape, its spread, or its center

                                        Image: New Item Type on Tuva

Over the last twelve months, we have received a variety of feedback from educators across math, science, statistics, and many other subject areas about being able to ask (and immediately grade) straightforward, multiple-choice questions at the beginning of the activity to assess for basic understanding, and then gradually build towards the more difficult, open-ended questions.

I am excited to announce that we will soon be adding these two new features - Multiple Choice Questions and Automatic Grading - to Tuva Activities and Lessons.

For Tuva Basic teachers, you will be able preview these new features via a number of different activities on the 25 Free Tuva Datasets.

For Tuva Premium subscribers, you will see this feature gradually introduced across all of our 400+ activities and lessons around 315+ datasets, as well as many of the new activities and lessons we release moving forward.  

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Introducing An Easier Way to Filter & Find Datasets on Tuva!

There are 300+ Tuva Datasets in our library covering topics such as the Climate Change, Land & Sea Animals, Presidents of the United States, and many many more.

Today, we are excited to do an initial launch of a more powerful Filter Bar to meet the diverse needs of our educators within the Tuva community.

A More Powerful Filter Bar:

Now, if you wanted to find all the Science or Environment-related Tuva Datasets that are small in size, you can find them very quickly by choosing Science & Environment in the Subject drop-down and 1-40 in the Size drop-down, like this:

As you can see above, you can now filter and find Tuva Datasets based on a number of additional parameters beyond Subject & Grade Level such as:

The Size of the dataset (How many data points are there?)

The NGSS standard (particularly relevant for all our US Science Educators)

The dataset Language (For our non-English speaking educators and learners)

Now, if you wanted to find all the Science or Environment-related Tuva Datasets that are small in size, you can find them very quickly by choosing Science & Environment in the Subject drop-down and 1-40 in the Size drop-down, like this:

Or, if you wanted to find a dataset that is related to the MS-ESS3-5 (Earth & Human Activity) NGSS Standard, you can find it very quickly by choosing MS-ESS3-5 in the NGSS drop-down, like this:

Send Us Your Favorite Datasets & Win

Do you have a favorite dataset that you have used in your previous lessons or units? Does it come from an authentic source? Is it licensed under Creative Commons? Are you able to link to it?

Send us your favorite datasets to [email protected] over the next two weeks and enter a chance to win a Tuva T-shirt, a Tuva Coffee Mug, and other goodies!

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What does NGSS look like in the classroom?

By Stephen Farnum - Middle School Science Teacher, Greenwich Public Schools & Tuva K-12 STEM Content Specialist

When I speak with fellow educators about Next Generation Science Standards, they usually tell me they understand “what” NGSS is, but have concerns about “how?”. 

How can I help my students meet these expectations? How does my instruction need to change? How am I going to find resources to help?

Tuva is on a quest to help science educators implement NGSS in their classrooms through our growing library of authentic datasets, interactive graphing tools, and ready-to-use activities and lessons. 

One aspect of this is to make it easier for teachers to create their own high-quality, NGSS-aligned lessons. 

In support of this, I recently collaborated with them to create Characteristics of an Effective Data-Driven Science Lesson, a checklist for teachers to use while creating or improving data-driven lessons which combine science, math, and problem-solving. 

I combined input from the NGSS Science and Engineering Practices as well as what I’ve learned from my students as they have developed their understanding of science and math through data analysis.

Once we completed the checklist, we realized that many teachers would like to see these characteristics of a data-driven science lesson in action.

Exemplar Science Lesson on Tuva

I created a lesson titled “How to Mitigate Hurricane Damage” to show one way of applying these characteristics to create an NGSS-aligned learning activity on Tuva.

I began with NGSS Middle School DCI: 

“Analyze and interpret data on natural hazards to forecast future catastrophic events and inform the development of technologies to mitigate their effects” (MS-ESS3-2). 

I searched the Tuva Datasets library to find a dataset titled - Hurricane Sandy, Her Brother and Sisters - that was relevant to the DCI. The source of the dataset is NOAA’s National Climate Data Center, and it has 654 Data Points (or cases) and 7 Attributes. 

I used Tuva’s graphing tools to explore relationships between different attributes. Noticing correlations between hurricane latitude, frequency, and severity, I designed a task that would guide students to investigate these relationships: 

“Create an evidence-based proposal for where a new hurricane mitigation structure should be placed” 

You can checkout the finished activity here, and feel free to use it in your classroom during your next Earth Science activity! 

Tuva NGSS Resources

The ability to easily find and create open-ended and student-centered learning activities shows Tuva’s potential as a tool for aligning K-12 STEM curricula with NGSS. 

If NGSS leaves you wondering “how?”, Tuva’s NGSS resources are a great place to start.

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Introducing Tuva Collections

At Tuva, our goal is to make data accessible and usable for data novices and learners, enabling them to learn and master foundational data, statistics, and analytical concepts and skills.

The Open Data Movement has catalyzed something incredibly powerful - free, open access to millions of datasets from a vast number of organizations such as the World Bank, NIH, NASA, CDC, NOAA, FDA, Census Bureau, Department of Education, Department of Energy, and many many others. 

We believe that these open datasets can serve a powerfully unique purpose. These datasets can be transformed into opportunities for deep inquiry, exploration, and learning. They enable educators to teach and students to learn critical data exploration, visualization, analysis, and interpretation, as they dig deeper into topics aligned to their curricula and standards, their interests, or their day-to-day work.  

To continue to realize on our vision, we are excited to formally announce the launch of Tuva Collections! 

What is a Tuva Collection?

A collection is a group of ready-to-use datasets, activities, and lessons around a specific content area (such as Linear Models) or topic (such as Social Justice). 

How many collections are on Tuva?

Currently, we have 4 Tuva Collections (and plenty more in the works!). They are:

1. Signs of Change - Discovering events and phenomena in US History using US Census Microdata

2. The Model Shop -  Using data to learn about Linear Models

3. Civic Literacy Through Data - Explore social issues including gender equality, gender identity, immigration, and racial justice in the United States through the lens of data

4. Employment in NYC - Exploring Employment in NYC through the lens of the 5 Boroughs, Race, Educational Attainment, Gender, and many other factors

Are you open to collaborations to create a new Tuva Collection?

Yes - we have many more Tuva Collections in the works so please stay tuned! 

We are already working with organizations such as Democracy Prep Public Schools and NYC Department of Education to design and produce our Tuva Collections. 

If you are interested in collaborating with us to create a Tuva Collection, please reach out to us at [email protected]. 

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Introducing the Model Shop - Enabling Students to Learn Modeling

From the CCSS Standards of Mathematical Practice - Modeling with Mathematics practice:

“Mathematically proficient students can apply the mathematics they know to solve problems arising in everyday life, society, and the workplace. In early grades, this might be as simple as writing an addition equation to describe a situation. In middle grades, a student might apply proportional reasoning to plan a school event or analyze a problem in the community. By high school, a student might use geometry to solve a design problem or use a function to describe how one quantity of interest depends on another.” 

From the High School Common Core Standards on Modeling:

“Modeling links classroom mathematics and statistics to everyday life, work, and decision-making. Modeling is the process of choosing and using appropriate mathematics and statistics to analyze empirical situations, to understand them better, and to improve decisions.”

From Science and Engineering Practice in the NGSS - Developing and Using Models practice: 

“Models include diagrams, physical replicas, mathematical representations, analogies, and computer simulations. Although models do not correspond exactly to the real world, they bring certain features into focus while obscuring others. All models contain approximations and assumptions that limit the range of validity and predictive power, so it is important for students to recognize their limitations.” 

Building on our Signs of Change content initiative that brings history and mathematics together for students, we are excited to announce the Model Shop, our next math and science content initiative dedicated to an incredibly important concept – Modeling.

The Model Shop contains Tuva datasets and activities that enable your students to build a strong foundation about Modeling. Students get an opportunity to use elementary, linear functions to make mathematical models of real data. 

Through our activities and lessons, students will get an opportunity to answer the following questions - What is a mathematical model? How is a mathematical model developed? How does the mathematical model represent our reality, and what is the meaning behind the curve and the parameters? 

We are starting the Model Shop initiative with linear models, giving students an opportunity to create a model for data related to a pencil sharpener, book pages and thickness, Chinese trains, Hooke’s law, and others. Over time, we will continue to add datasets and activities beyond just linear models, including logarithmic, quadratic, exponential, and others. 

All the Tuva Datasets and Activities in the Model Shop are fully accessible only to Tuva Premium customers. Learn more about Tuva Premium here or get in touch with us directly.  

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Introducing Signs of Change - Discovering Events & Phenomenon in US History Through Census Data

Today, we are excited to launch a brand new content Initiative called Signs of Change on Tuva. The overarching goal of this initiative is simple, yet incredibly powerful. 

We want to empower learners to discover events and phenomenon in US History - events such as the Civil War, the Great Migration, the Rise of Women in the Workforce, the Baby Boom, and many others - by enabling them to explore, visualize, and analyze US Census Data from 1850 - 2000. 

The US Census 

It’s worth to take a side journey and learn a little bit about the US Census. The US Census is a decennial census, and is mandated by Article 1, Section of our Constitution. 

The first Census after the American Revolution was conducted in 1790 (under then Secretary of State Thomas Jefferson), but the 1850 Census was the landmark census in that it was the first time the Census Bureau attempted to record every member of every household, including women, children, and slaves. To note, the population of the US in the 1850 Census was 23.1 million. 

The last Census took place in 2010, and it was the first time the US population exceeded 300 million!  

A Dance Between History & Mathematics 

The Signs of Change Initiative is a unique opportunity to connect history and mathematics for learners, enabling them to use foundational mathematics and statistics concepts to topics they are learning in their history class.  

For this initiative, we plan to curate a variety of datasets from the US Census Microdata from 1850 - 2000 over the coming weeks. In addition, we will make available sample activities and lessons around these datasets that you can use immediately, or that you can modify to make them appropriate for the needs of your students.  

Extending this Approach Beyond US Census

We strongly believe that this approach can be adopted well beyond just the US Census. The Census is a powerful instrument that countries around the world use to acquire and record information about their own citizens.

For all our educators outside the US – if you are interested in bringing this kind of an initiative with the Census data from your country, please submit your thoughts in Discussions or write to us directly.  

Attribution 

The initiative has been adapted from an actual book called Signs of Change, originally compiled and edited by Dr.Tim Erickson. The book stems from a collection of statistics projects his students conducted at Lick-Wilmerding High School in San Francisco, CA in Fall 2011. 

We would like to express our sincere gratitude to Dr.Tim Erickson and all the students who participated in the original project. 

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Announcing Tuva Premium for Schools, Districts, and K-12 Organizations

Over the 2014-15 school year, teachers and students in thousands of classrooms across the country and around the world used Tuva to bring relevant topics, authentic datasets, and data-based, inquiry-driven activities, and lessons to their students. 

Since we released the “Upload Your Own Data” feature in January of this year, educators and students have uploaded thousands of datasets for their math and statistics classes; biology, chemistry, and physics labs; and for a variety of projects on Tuva. 

Checkout some of the testimonials to learn about the the kinds of powerful, memorable learning experiences educators are able to create for their students on Tuva. 

Today, we are excited to officially announce the launch of Tuva Premium to further empower educators to teach and students to learn critical data literacy skills.

The basic version of Tuva (Tuva Basic) will remain 100% free for all educators and learners. Tuva Premium will bring a number of additional, powerful components across content, graphing, insights, and support services for our school customers. 

What are the differences between Tuva Basic and Tuva Premium?

Tuva Basic will remain free for math, science, english, social studies, and other educators and learners around the world. As an educator, you will be able to create your own classes, enroll all your students, and assign and grade activities on Tuva. 

With Tuva Premium, you will get:

1. Access to our entire bank of curated datasets and inquiry-based activities and tasks.  

2. Comprehensive Student-level and Class-level insights into their growth and progress.

3. Unlimited Dataset Uploads for all teachers and students. 

4. Dataset Requests, and dedicated on-boarding and ongoing support. 

Checkout Tuva Basic and Tuva Premium for additional details. 

Public, private, charter, and parochial schools around the country have already purchased a yearly subscription to Tuva Premium for the 2015-16 Academic Year. 

If you have any additional questions or would like to purchase Tuva Premium for the 2015-16 School Year, please write to us or call us at +1.646.481.2150. 

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Introducing Interactive Data Courses on Tuva

At Tuva, our mission is to make data and statistics accessible and usable for data novices and learners around the world. We believe that the best way to learn data and statistics skills and concepts is by actually getting your hands dirty with the data; exploring, analyzing, visualizing, and interpreting it in a variety of ways and across different contexts.

To realize this vision, we have built Tuva - a powerful learning platform that brings together:

1) Curated datasets from authentic data sources

2) Dynamic, easy-to-use, yet powerful data analysis and visualization tools, and

3) Inquiry-based, highly engaging lessons and tasks.

Educators and students in over thousands of schools and hundreds of higher-ed institutions in over 70 countries use Tuva in a variety of different ways in their classrooms.   

Today, we are announcing another significant addition to Tuva. We are excited to collaborate with some of the most reputable organizations, institutions, and instructors in the world to bring to you hands-on, interactive data literacy courses on Tuva.

These courses will empower people working across education, healthcare, international development, and other sectors to learn and master foundational data and statistics concepts and skills that will be relevant to their work.

We are actively working on the interactive course design, the content, and the appropriate credentials for the first set of courses on Tuva. Subscribe to receive updates as we launch courses on Tuva. 

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New Feature: Plotting Multiple Numerical Attributes on the Same Axis

When it comes to exploring data, how one organizes the dataset is incredibly important. Typically, each column should represent an attribute and each row should represent one observation. There are certain best practices one should follow when organizing a dataset, but we will leave that for another post.

There are times when the data is organized a bit differently, one needs to be able to plot multiple attributes on the same axis in order to meaningfully explore and analyze the data. Today, we are launching this functionality on Tuva.

Once you drag and drop an attribute on the x- or y-axis, you will be able to drag another attribute and drop it on the small rectangular box that appears below the attribute on that same axis. Here is a brief video showcasing this new feature in an example:

What do you think about this feature? Take it for a spin on the Climate Change or World Populations dataset, and post your comments, ideas, or feedback in the discussion thread.   

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Tuva Labs is now just Tuva.

Today, we are announcing a brand refresh of Tuva. As part of the refresh, we are officially dropping the “Labs” from our brand. 

Tuva Labs is now just Tuva.

Data novices, educators, and learners from around the world are joining the Tuva community everyday to find curated, open datasets; use our dynamic, easy-to-use data analysis and visualization tools; and learn our interactive data-base activities and tasks.

As part of this refresh, we also have a new logo!

Let us know your thoughts on the new logo in the comments, and enter for a chance to win a brand new Tuva t-shirt or coffee mug!   

Our mission is to build Tuva into the premiere data literacy platform, making data and statistics accessible and usable for data novices and learners around the world.

We are continuing to make really good progress to bring our vision to fruition, and are excited for the next stage of our journey and growth.

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Teacher of the Week - Dave Ferris

David Ferris AP Statistics, Precalculus, Finite Math Noblesville High School Noblesville, IN

"Tuvalabs is a refreshingly high-quality and engaging web-based tool for my students (who all have iPads). The datasets are interesting, and the analysis tools are easy to learn. I love the ability to create my own activities and have students complete them side-by-side on the same screen with the analysis tools. Tuvalabs is the perfect tool for introducing students to the excitement of discovering the stories that data can reveal."

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Teacher of the Week - Jodie Deinhammer

Jodie Deinhammer High School Science, Anatomy, and Physiology Teacher Coppell High School Coppell, TX

“Over the last few years, I have searched for ways to incorporate data analysis into my senior level Anatomy and Physiology course.  Stumbling across Tuva was one of my favorite finds of the year.  

This year, my classes were able to analyze the use of vaccines in society and support their claims of efficacy with evidence obtained from Tuva.  They could clearly see the correlation between vaccination rate and disease.  They also discovered an outlier in the data which generated engaging class discussions and interesting perspective on disease, society, and income.  

Students need to be able to manipulate data, extrapolate information, and make informed decisions in order to develop evidence based conclusions in science. TuvaLab gives educators the ability to provide this to our learners with its user friendly interface and customization.”