Local Data & Tuva - Using Local Data to Foster the Science Learning You Want

Students are more interested and engaged in their learning when it is centered around topics that have relevance to their lives.

Therefore, integrating local examples and phenomena into instruction is a natural way to maximize student engagement. There are many ways to integrate such examples into your instruction (e.g., articles, videos).

We see value in diving into local data to leverage the learning you want to happen in your classrooms and thus work to support uses of local data in classrooms throughout the country for a variety of reasons.

How can I use Tuva to leverage “local data” in my instruction?

So, if you are studying a particular widespread phenomenon (e.g., weather) explore it using data from where you live, rather than from far away. Tuva provides a wide range of curated datasets -- like weather, earthquakes, river flow, air quality, sea-level and day length -- to help make that possible.

Let’s explore some examples we currently have:

If data from your region of a widespread phenomenon is not included in a dataset, it could be! Let us know and we will work to find it for you.

 

If you are focused on learning about a local 'place' or comparing places, students can investigate datasets about local issues, events, and phenomena. Tuva provides a wide range of such curated datasets, many of which have been requested by educators in different locations.

We have LOTS of datasets that are local to cities, states, and regions:

We have many datasets that are designed to, or make it easy to, compare among different locations, such as:

 

There are some phenomena that are uniquely connected to one particular location (e.g., geyser eruptions). At Tuva we provide a range of such datasets as well for you to explore.

Check out some of these cool examples:

If there is an interesting uniquely local phenomenon in your area that we don’t yet have a dataset for, it could be! Let us know and we will work to find it for you.

 

Whether they collect data in their classroom or community, or find data collected by a local citizen's group -- it only takes a few minutes to upload it and visualize results. Check out our Importing Your Data into Tuva resource for more details. 

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What is meant by “local data”?

Many agree that it makes sense for students in Arizona to study the concept of abiotic and biotic relationships by exploring data from desert ecosystems. But it would likely be more meaningful for Michigan students to study abiotic and biotic relationships using data from northern hardwood forests or from Great Lake ecosystems than the desert ecosystems.

Thus in one instance, local data can be leveraged for deeper learning of issues, phenomena, and/or processes by using data from where you live and what you are more familiar with. Rather than looking at data from across the country or from a different country (i.e., a place your students may have no experience with), use data from your schoolyard (or town, county, state, etc.) to investigate the issues, phenomena, and/or processes.

Similarly, you can use data local to your area to leverage your students understanding of the surrounding area to more deeply gain a sense of place, and potentially how it compares with other places.

Another way you can leverage your students learning by using local data is when a phenomenon is unique to a specific location, in other words it is a localized phenomenon, and thus to investigate that phenomenon you need data from that area to understand it. Rather than just reading about it, dive into the data to explore it!

Additionally, you can use local data to more deeply teach the process of science as your students collect their own data to explore their questions.

At Tuva, we support all ways to leverage learning for what you want to happen by using local data. Use Tuva’s search filter to find "local" data for your students using key words or names for the places, issues, and phenomena that your students care about or you want to bring into your teaching.

 

Because “local data” is often more about relevance and meaningfulness than about a physical boundary, it means that “local” data can pertain to different geographic scales. So, for example:

    • When studying about the growth, development, and reproduction of organisms:
      • You could look at how the behaviors of cardinals affect their probability of successful reproduction, so local would be the area around the schoolyard (and maybe beyond) that the cardinals use.
      • Also, you could look at how the behaviors of moose in your state affect their probability of successful reproduction, so local would be the area of the state that the moose use.
    • When exploring weather and climate:
        • You could look at how weather in a certain location changes over time (e.g., your school), so local would be the area around the schoolyard determined by where your data collection instruments are setup.
        • Also, you could look at how air masses flow from regions of high pressure to low pressure and how that causes the weather in a certain location to change over time then local is the broader region around your school that air masses move through.

Additionally, studying “local data” at different geographic scales provides a great opportunity for students to articulate their understanding of the crosscutting concept of scale.

 

Local data comes from many different sources, both primary that you collect yourself and secondary that others collect but you use. At Tuva, we support and draw from the following sources for our datasets that can be used to leverage your learning objectives:

  • Your students collect their own data.
  • Citizen science projects around the world collect data for a wide range of issues, phenomena, and processes. If any exist in your area, consider using the data and potentially getting your kids involved as citizen scientists themselves.
  • Scientists at various town, county, state, and federal agencies collect data related to their agency’s mission. These data are paid for by taxpayers dollars so they are available to access. Many are already online, but you can also email an agency and request data you cannot find online.
  • Scientists at universities and research institutions collect a wide range of data for their research, which they publish in peer-reviewed science journals, and often make available through online databases. If you learn of published research that you would like to find data for, you can email a scientist to find out how to obtain a dataset. Often scientists are excited to share their data for educational purposes, but know that there can be time lags due to research and publication schedules.  

Finding and collecting data can be time consuming which is why we provide an ever growing number of curated datasets from these sources for you to use more easily! If there are data or issues that we don’t yet have a dataset for, let us know and we will work to find it for you.

 

 

Why use “local data”?

Local data can be used as a hook to engage and motivate students to begin to explore a concept, to build your students data literacy and process of science skills, to explore issues that matter to your community, to understand how your place fits into a wider context or system, to explore how where you are compares with another place with regards to a phenomena, and many more. But what does research say about why we should focus on local data?

First, research indicates that students learn more overall, in more depth, and retain their learning longer when they have ownership of their learning (National Research Council, 2012). And the quickest way to help students develop that ownership is to have them collect the data themselves. Then they know the ins and outs of the data, and especially when they have identified the question to ask and how to go about answering it with data. So, one great reason to use local data in your teaching is that we know students are more connected to, empowered by, and engaged to learn from data they have collected themselves.

As we know though local data is not only data your students collect themselves. There are numerous professionals and citizen scientists in your area who also are collecting data related to issues, phenomena, and processes in your area. Fortunately, research also indicates that students are more motivated to learn and engaged in their learning when they investigate something that has relevance to their lives (Achieve, Using Phenomena, 2016). And what better way to connect the dots of your content and their lives than to use data from your area to explore the issues, phenomena, and processes?

In essence it is a win-win-win to using local data: it makes the learning relevant, it connects students to their local place while learning, and it builds their data literacy while following successful pedagogical practices!

 

Three dimensional teaching with NGSS is grounded in phenomena, ideally those that are observable and interesting to students. We know that students are more interested and engaged in their learning when it is centered around topics that have relevance to their lives. Therefore, using local examples of phenomena is a natural way to integrate phenomena-based instruction in ways that maximize students’ engagement in their learning.

There are different ways to integrate local examples into your instruction. You can incorporate local stories through text to provide context of an issue as you explore learning experiences that teach the concepts. However another option, that NGSS heavily encourages, is to dive into local data to build a conceptual understanding of the phenomena.

Also, using local data can provide a uniquely relevant context to authentically integrated the Crosscutting Concept of Scale, Proportion, & Quantity into your instruction. Each time students look at local data or compare local with larger-scales they will be exploring the concept of scale.

 

References

  1. Achieve, Inc (2016) Using Phenomena in NGSS-Designed Lessons and Units. Retrieved from: https://www.nextgenscience.org/sites/default/files/Using%20Phenomena%20in%20NGSS.pdf
  2. National Research Council (2012) A Framework for K–12 Science Education: Practices, Crosscutting Concepts, and Core Ideas. Washington, DC: The National Academies Press  https://doi.org/10.17226/13165
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