Announcement

Introducing the first Tuva Science Collection — Earth in Space

earth-rising

Here a star, and there a star,

Some lose their way.

Here a mist, and there a mist,

Afterwards — day!

Few have conveyed the beauty of dawn with more inspiration than Emily Dickinson. As teachers of Earth science, we aspire to convey to students appreciation and understanding of what it means to be a planet moving through space and how our position and movement in space predictably affects our everyday experience of, well — day!

The magnitude of spatial and temporal scale differences covered by the topic of “Earth in Space” makes it challenging to find datasets about stars, planets, Sun and Moon, orbits, seasons, tides, and day-lengths that are of a scope that students can explore to find meaning and discover patterns and relationships.

At Tuva, we are gathering datasets into collections by topic to help you quickly find data and activities that support a unit you are teaching. Our first Tuva Science Collection is Earth in Space.

Tuva’s Earth in Space collection provides opportunities for students to analyze and interpret data and model systems (see NGSS ESS1.A and ESS1.B) to support understanding of key ideas such as:

Stars range in size, type, and distance from our Solar System.
Planets have different properties (density, gravitational pull, orbital period, temperature…)
Seasons occur at opposite times of year in northern and southern hemispheres.
The timing of tide cycles can be explained (and predicted) by the phase (and position) of the Moon.
How much day length changes through the year depends on latitude.

Each dataset has at least one activity, and you can add or adapt activities to fit your teaching goals.

Help your students discover and appreciate the music of the spheres — through data!

We will be adding many other science collections in coming weeks and months. If there is a collection you are especially interested in, please let us know via Tuva Support or share with the community on Tuva Discussions.

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!

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.