Welcome to Real World, Real Science! This NASA-funded project aims to leverage investigations of ecosystem change as a compelling context for building middle school students’ data knowledge, skills, and dispositions. This school year is our summative evaluation year, interrupted of course by school closures this spring. Our video therefore focuses on two key project aspirations: 1) to enable students to work with authentic data derived from NASA’s Earth sensing systems (for example, global sea surface temperature) alongside locally collected data (for example, state data regarding populations of key species); and 2) to meaningfully connect informal and formal learning experiences and leverage the best of both. We are eager to hear from others about lessons learned creating connected learning ecosystems and about the use of authentic, MESSY data with this age student.

Our team is particularly interested in discussion around questions like:

1. What successful and scalable mechanisms are you aware of for meaningfully connecting students’ experiences inside and outside of school?

2. What approaches (resources, tools, educator support) have you seen that effectively support students to evolve from analysis of small, personally or locally collected data to larger data sets collected by professionals or by remote sensing?

3. What student outcomes related to data and climate have you documented, and what measures have you used?

Looking forward to our conversation!

I love the connection you make between the skills we teach youth and how it translates to critical thinking adults.  I look forward to hearing what people add to this comment thread related to the evolution of working with small local data sets to larger collections of information. I am personally very curious about this. 

I love seeing the interactive nature of your data sets and seeing how the youth physically get to touch it and write on it by using the touch screens.

You are doing great work.

Perrin

 

Thank 

I liked your video and the concept of engaging 5-6th grade Maine students with data about local ecosystems and species that they can relate to.  How could they not be interested in this? I would think this could be applied to higher grade levels too. Well done.

Dave

 

Hi Leigh, This is such a great project! It is critical to be educating the next generation of citizens about such important, societally-relevant science and helping them to develop data literacy at the same time. We have found that data related activities in themselves are greatly enhanced when the students can collect their own data, in our case oceanographic data. We usually work with older students, and I commend your project for engaging middle schoolers. 

There is so much to love about this project! Keeping it local, keeps it personal and keeps kids invested. And then there's the 'messy data' - looking forward to the discussion that unfolds in this thread. 

What a great opportunity for students to connect real data with what is happening in the world around them! I'm curious about your strategies for helping students make sense of data. What difficulties did students have in connecting what they see on a graph to real phenomena? How did you help them bridge the divide?

This is some pretty sophisticated stuff going on with the kids--a great statement about what young students can do when given inspiring resources. I wonder how this goes when you get back in the classrooms. It sounds like you've got some committed pilot teachers. How did you engage with them? Are they connecting what is going on to the standard curriculum (i.e. what other classrooms are also covering), or is this a particularly enriched curriculum that is in addition to what they would normally cover?

Seeing the students and teachers doing the activities in Real World, Real Science is truly motivating.  The activities look amazing.  We must figure out a way to include the activities with SEES.  Great job!

Leigh and team, amazing project--love the data/analysis "tinkering" that youth get to engage in with peers and experts! I am interested in how much you make the MESSY data a programmatic element. If I think of our own work we spend a lot of time collecting, cleaning, merging data (maybe that's 80% of what we do!) then the actual analysis/synthesis phase takes much less time... to me that is authentic science. I guess that might be one strategy to link the informal and the formal or the personal to the professionally gathered data--to lean into the data cleaning and merging strategies; though not the most exciting process--might have to give it some drama for 5th and 6th graders?

Hey Scott and thanks for the comments/questions! You're right -- somebody somewhere is going work with messy data to make it feasible for kids to work with it and derive meaning. We spent HOURS talking about this and viewed it somewhat through an ethical lens with a concern that if we clean things up entirely we take away the reality that the stories kids are working on are not yet "done" so there is openness for patterns to emerge other than the ones we might highlight in the cleaning and processing. We deal with it very directly when kids are working with small (very small) data sets. "Why did your group come up with a different measurement than mine and what do we do about it?" When they're working with professionally collected data that is still sized to be manageable within, say, a single data table, we start talking about patterns and outliers. For the large data sets (e.g., sea surface temperature) we chose to use the data points that most dramatically show the overall trend (e.g., September average SST over time). I think the point you're making about figuring out ways to expose kids to the sorting, filtering, cleaning "moves" that are part of working with big data. I've been thinking a lot about whether the sorting, filtering, cleaning we can reasonably get young kids to do with smaller data sets is even the same kind of thing as what they'll do later -- is it actually a continuous growth line from the early application of those moves to more sophisticated ones? Or is there some other kind of work that has to happen to jump to the more sophisticated work? I know there are other projects thinking about that also so hope they weigh in here!

This project includes two important topics, understanding the effects of climate change and interpreting data.  You mentioned the PD for teachers, but I’m curious how much preparation the students have before they visit GMRI, and if they spend more than a day there.  It’s great to see there’s an extensive follow-up in the classroom

What a great project!  It is good to see the integration of in-classroom, and informal venue experiences as learners develop a more complete model of natural phenomena.  Ensuring the field trip is more than a novel experience outside the overall curricular experience is essential.  Something we strove to do in our own project.  Thank you for sharing!

I don't mind echoing the praise that others have given you for this project. It's really wonderful. I especially like the emphasis on the personal effects of climate change -- how one's community is being and might be impacted. What have you learned from students? What beliefs and ideas do they bring to their lab work? What general advice do you have about how to leverage students' community knowledge in learning situations?

I'd also like to echo praise for this project. I don't think I have anything to add that someone hasn't already said about the great work you're doing.

I'm wondering if you've heard of students turning their learning about locally relevant data into service learning projects. 

Also, you may already be aware of this, but we worked on a really interesting collaboration with Rutgers and Padilla Bay National Estuarine Research Reserve to help teachers engage students with locally relevant data and improve their data skills. You can find some of our resources here: https://mare.lawrencehallofscience.org/curriculum/climate-data-aclipse-activities

Thanks for sharing this very exciting project!

It is projects like these that honestly reinvigorate my passion for informal education and getting students interested and hooked on science. I am especially excited as I know and appreciate GMRI and Lab Venture's efforts, and can only imagine an expanded, revamped program!

I have throughly enjoyed reading the discussion above, as I had similar comments and questions, and your responses have been informative and interesting- many thanks for that!  The PD you are offering where you are letting teachers choose which module they'll do and in small teams walking through the content, co-learning and in many ways co-developing as they make adjustments is really key (and fantastic!!). Many teachers, especially elementary school teachers, are data shy or even science shy (even though it is being integrated into elementary school standards now), so getting them familiar with the data and analysis processes will only make it easier for them to transfer knowledge to their students in the classroom and efficiently work though things. One question though with regards to standards, have you felt any push back from teachers about how things can't fit?  I know that you mention above teachers work to make things that they choose "fit" into their curriculum (having insight, of course, as to which will work best in their classroom setting), but have you found some modules "plug and play" easier than others, and what about those modules makes them easier for curriculum integration- is it they focus on a topic that aligns really well with a NGSS standard, or that they cut across math, social studies, etc., or perhaps both? 

Have you also thought out student ambassadors as an extension of the project? Or perhaps a culminating poster session of sorts (which could now be done virtually), where students from different classes/groups are able to display and discuss the data they have worked with and receive feedback from other groups. This would be another set of skills that could transfer to life skills and a student's general career pathway. Just curious how you round things out for the students as they complete your program.

Thanks again for all your hard work- it really is fantastic work you all are doing!

Hi Holly! Thank you so much for your question, and for your interest in this work!

Regarding standards, as we started developing the program and the curriculum modules, we surveyed a variety of different resources for information about relevant data skills to be teaching at this age, including NGSS, CAT, CCSS, etc., and from these, we came up with a condensed set of priority data skills that we wanted to teach through the experience and the curriculum:

Collecting and Decoding Data

• Identifying structural components of data representations (e.g., axes on a graph, table rows and columns, scale on a map, color key)
• Identifying and extracting data values and what they represent from graphs, tables, maps, or other representations

Analyzing, Interpreting, and Communicating with Data

• Choosing appropriate visualization
• Identifying and describing features and patterns (e.g., variability, trends, anomalies)
• Making and/or manipulating models
• Explaining meaning of observed patterns
• Making and supporting claims with evidence

Critical Thinking with Data

• Evaluating strengths and limitations of hypotheses, claims, or models
• Acknowledge and appraise multiple explanations for observed features and patterns in data

We also recognized that not all topics will "fit" in all classrooms, so we've tried to come up with a range of topics in hopes that at least one might find a comfortable place to land. We have a couple of modules that focus on marine ecosystems, but we also cover ticks and Lyme disease, ice-out dates on Maine's lakes, and are working on new modules around lynx, blueberries, loons, and potatoes. 

Our hope is that by creating materials around a variety of locally-relevant topics, and aligning the data skills with a variety of state and national standards, we make it easy for teachers to find ways to fit them comfortably into their lesson plans.

Regarding student ambassadors - I love that idea! I think that the idea of students sharing their work with others is a great "next step" in building these kinds of skills, and I'd love to learn more about successful models that others have used to do this!

I really enjoyed your video and project! As an oceanographer, the topic is very close to my heart lol!

I see the detailed standards you are addressing through the project, by I'm curious what assessment tools are you using to measure how the lessons are meeting those standards. Are the students attending these sessions as field trips where you can do pre/post testing, or are you using any software to track their movements on the smart boards?

Have you considered analyzing their ability to interpret the visualizations at different levels of understanding, such as: elementary level of identifying data points, intermediate level of identifying trends in the data, and advanced level of identifying patterns not implicit? 

Wonderful project! I especially appreciate the place-based aspect and the intention and understanding on the part of your team that these same kinds of interpretive skills may follow students throughout their lives as they "interpret complex news stories" and make future decisions.

 

 

Thank you, Catherine! We love M'Kenna!

I appreciate your work with around sensemaking with data, especially connected to climate science/change. Have you been able to or thought to publish any of your curriculum approaches in the NSTA journals?  I am only asking, since I think there still exists a shortage of resources to support teachers in this area. Thanks for sharing your work!

What a great project. It had me wondering about broader applications. How challenging would it be for educators in other states to adapt this approach to what's happening in their own students' back yards? 

I'm really glad you asked, Michael. This was an aspect of the project that hit the cutting room floor. Simultaneous to our work in Maine we've been fortunate to work with a network of small science & technology centers across the northeast who have been working through their own approaches to the fundamental premises of the project -- connecting informal & formal learning and using climate science as a focus for supporting explorations of data. Their work has been SO creative. For example, the Montshire Museum in Norwich VT spearheaded development of a ticks & Lyme exploration that starts in a much more hands-on way, looking at ticks under the microscope and identifying species of ticks. They even made a public engagement exercise out of collecting the tick samples (and got enough to send collections around to all the other museums in the network!). This leads into looking at their local state data on Lyme disease and they were able to offer their teachers the Ticks & Lyme curriculum developed for the project in Maine. We haven't tracked uptake of the curriculum in other places, but will be doing that going forward. My cautionary tale: at the heart of each narrative is a local phenomenon (e.g., patterns in blueberry production), for which we have solid local data (from a UMaine Extension agricultural scientist), that has a strong climate signal ("cooling" days), for which we also have data (temperature data over the winter months). Those stories have turned out to be remarkably difficult to find, so not for the faint of heart.

I really liked hearing about how students can gather data and ideas in their Digital Field Notebook and then bring that back to the classroom with them.  That is a great strategy to help teachers support students in continuing to work with the ideas and make meaning that will be durable over time.  

This project is terrific.  I also am a big fan of the digital field notebook idea. Are there things you have learned about what practices tend to encourage this kind of sustained participation after the in-person interaction? Seems like an important thing for us all to learn from as we chapterize and connect different kinds of experiences together in our new normal.  Thanks for sharing this video and for the great work!

Great work!!  

Leigh, this is such great work. I am so glad it is progressing so well. Since there is a real place-based element to it, has there been much focus on either of the following:

1. How to use this as a model to do this work across the country  (particularly in coastline regions)
2. How to make this accessible to students who can't do a physical field trip?

The answers to these questions could be so valuable in our project as we think about STEM ed for those who are incarcerated. 

Wonderful work. Hopefully. I can come up again sometime when we are not sheltering in place to see you and GMRI. 

Eden

Thanks for the questions, Eden! We've been working with a fantastic network of 12 science & technology centers across the Northeast in this project. Each has interpreted the goals and work in their own way, but in the next stage of the work we hope to focus more deliberately on what constitutes "the model" and how we can support it to be versioned organically elsewhere. 

For purposes of serving students & teachers during the panedemic, we created a "virtual" version of the field trip where we have taken over teachers' classrooms for five days (1 hr/day) to engage kids with the heart of the content. It's been extremely well received, including involvement by schools who haven't ever come over our 15 years of delivering the program. That leaves us with quite a challenge: should we offer it virtually AND in-person going forward? The trip is entirely free (we pay for transportation) and for many kids in Maine it's they're first time outside their home county, first time to the ocean, etc. and for nearly all it's their first time to a scientific research institution. We've always felt that had such incremental value that we didn't want to risk reducing in-person visits by offering virtual. But this time has given us pause. It's time to rethink.

Already looking forward to whenever you get to visit!

Very neat tool.  S'great that students can connect their museum experience to the classroom.  Curious about the museum experiences.  Are the museum collaborations of kids using Real World Real Science?  In our work, we also provide a technology for learners to collaborate and would love to see, hear, know more about how this tools creates and curates curiosity!

Wow!  Leigh, what a great project.  Since I am in landlocked Iowa, what do you think will need to happen in order to be able to take this project to scale across the US using different datasets and issues for different regions?  Is that a possibility?  Or what resources are available for new partnerships to take the technology and apply it locally?  How much of the project is open source?

You asked: 

1. What successful and scalable mechanisms are you aware of for meaningfully connecting students’ experiences inside and outside of school?

The GLOBE Program (www.globe.gov).  I see on one of their videos that you are a new GLOBE partnership - Welcome to GLOBE!  The variety of protocols available and the amount of data accessible makes it possible for students all around the world to ask and answer their own questions.  GLOBE community and online resources provide necessary support.

I think there are many other citizen science projects which, like GLOBE, give students access to the process and content of science in meaningful and feasible ways.

 

2. What approaches (resources, tools, educator support) have you seen that effectively support students to evolve from analysis of small, personally or locally collected data to larger data sets collected by professionals or by remote sensing?

I think there is a big need for this. 

On my campus, our Meterology Professor has had success engaging students and teachers in big NWS datasets thought learning to make weather predictions.  He built the STORM Project Website with a tool that verifies several different individual weather prediction strategies (persistence, climatology) and several models daily for several locations in our state.  Each student or pair of students can use the tool to enter their own daily prediction for high and low temperature and precipitation.  The tool will validate and score all of the predictions and rank the students and the various models and methods.  Students learn how to access NSF datasets in order to develop their own predictions.  In just a 3-4 week class almost everyone becomes better at making predictions that climatology - which is the definition of a skilled forecast.  I love this project not only because it introduces students to big data but also because it introduces them formally to predictive science.  They are motivated by the idea that even the teacher doesn't know the "right answer" or what will happen (which is often not the case in other field research).  Some classes plot the local weather report to see if they can do better.  They also learn that weather prediction still requires humans, each model works best at certain times and conditions for each locations - learning local patterns can increase your success!

 

One of the earliest examples of this strategy that I have experienced was several years ago (probably 15? or so). I took a tour of an Indiana DNR education program that connected students to state data sets through inquiry based field activities and an interactive website.  Teachers and students would do some pre-work, then go on a field trip where they would collect some of their own data (the activity I did involved each of us observing and collecting data at a local wetland and determining if the wetland would be a likely habitat for a specific bird), then using the DNR trailer's wi-fi, they would enter their data into the website.  All of the student data was combined with state data.  The students would learn which of their birds had been seen on the wetland that year and where in the state the other birds had been found.  Back at the school, the teacher would lead the students through additional activities that involved using the website to map all of the data and making a list of birds that the class would expect to find or not find in that wetland throughout the year. Then adding DNR bird count data to verify and look for trends in which populations were coming to the wetland.  Finally, they could overlay surrounding land uses and try to make sense of changes in bird counts over time based on their observations and historic data.

 

Great work and very happy I got to see it not only here but also "live", in the pre-pandemic age, long long ago.

What a great project! Wish there was something like this going on when I was growing up in the western foothills of Maine! I love that you are expanding the work to high schools and adults as well. I'm curious about future directions you are imagining for this work. 

Absolutely! My kids would have loved to be involved in investigations like the ones in your video.  I kept thinking, we need this here in MA!   We will most definitely keep talking. 

It's great to see LabVenture venturing into more complex inquiry skills. One question that always comes up for me is whether kids know the data is authentic, what they think that means, and whether it matters to them. In the museum world where genuine artifacts are so valued by curators, visitors often don't realize that the artifacts and sometimes their arrangements are "the real thing."

Sorry, I know it's an hour before shut-eye so no worries if you don't answer. Great project!

Yeah, thanks for tossing an easy one over the wall at the last moment! I know that this notion of "authenticity" is a curiosity of yours, so I'm not entirely surprised by the question. To be clear, our working definition of authentic is that kids are working on problems that haven't been solved yet in ways that are developmentally appropriate but still as close as possible to how our scientists do that same work. That actually excludes some data that is essentially the replication of known science -- we know a lot about patterns that emerge when balls run down various ramps, even if kids are collecting the data themselves.

We haven't included questions about kids understanding of authenticity, or its incremental benefit, in the evaluation, but I'm inspired to do so. The mechanism we use to be sure they know it's authentic is primarily video -- we show the scientist doing "the same thing." We show the scientist's original data, which becomes their data. So, for example, Marissa MacMahan is our black sea bass scientist and you see her recording the data in her notebook. We then digitally flow kids' data into the larger data set that is identified as coming from Marissa. We also work extremely hard on the script that supports the on-site Educators who are guiding the experience, and that script reinforces authenticity.

Do the kids get it? Does it matter? I want to say yes but I don't have the evidence to confirm. I know from personal experience teaching that kids can sniff out anything that is clearly NOT authentic. They know when they are replicating an experiment for which the teacher/educator already knows the "right" answer. But I don't think we've yet proven the incremental value of kids pursuing messy data that isn't yet completely understood.

Thank you for closing with this discussion of kids,  authentic data and messy data.  I look forward it continuing to scroll back to enable kids to be a part of building what data does for them and their interests over time.  It's been extremely helpful to read the week of discussion at this site.

Hi Randy, Thank you for providing the condensed set of priority data skills.