Daniels’ Teaching Case (WestEd)
Author: WestEd
As you read Questions, use the NowComment tools to annotate the text where you see:
- Important successes or challenges the educator encountered during the data lesson.
- Principle(s) of data-rich instruction (see comment bubble and Canvas for a list)
Collecting Primary Data Outdoors
I want my students to be “real” scientists. As a student myself, I got frustrated completing labs with an exact, correct outcome. No matter what topic we studied, I questioned, “If you already know the answer, why are you having us do this? Can’t we do something new?”
Now I teach seventh graders who may not have the same need as me for a unique research opportunity, but I still want to foster potential interests and plant seeds about what being a scientist is all about. To accomplish this, a favorite activity of mine is taking students outside to learn about their place in the natural world and participate in primary research.
An important goal of mine is to have students collect and analyze data. Many published curricular materials require students to use data from locations far from home but my intuition tells me students need an opportunity to use data from their own environment first. Each year, I always begin with a biodiversity unit intended to help students connect to their school environment and learn skills to help them become more data fluent.
Disappointing News
“I’m sorry, we don’t have school buses available for the dates and times you’ve requested. We do have a coach bus you could use instead.”
“How much will that cost?”
“Coach buses rent for $1,100 per day.”
“Is there a discount for schools that need buses on multiple days?”
“I’m sorry, no.”
“No thanks, then. I don’t think I can rationalize spending several thousand dollars to take my students outside. Thanks anyway.”
For the past 18 years, I have taken my students on a research trip to a 72-acre prairie restoration site that they have planted, helped manage, and observed. It’s an ideal place for students to collect data, document biodiversity, and use the data to help monitor the ecological effect of prairie restoration. The site is a beautiful property teeming with over 100 different species of plants, birds, insects, and mammals. My students collected data there, grew to appreciate the natural setting, and made lasting memories. They compared the data collected there to data they gathered in the schoolyard and used what they learned to suggest ways we could improve diversity at school..
I am determined to figure out a way to continue offering a primary research experience to my urban students. I teach multiple sections of science at a public, environmental-focused middle school where students are encouraged to explore their world and equipped to become agents of change. I believe it’s imperative for students to understand their place in the world and how their behaviors, habits, and actions impact it.
Setting Data Goals
Collecting primary data meets so many data goals I have for my students by inviting them to:
- Engage in the practice of “using mathematics and computational thinking”
- ”Own” the data because they know exactly where it comes from and easily relate to it
- Access a strong pathway for data science
- See the intersection of math and science as they add large sets of numbers, calculate percentages, and construct plots to uncover relationships between organisms and their environment.
Faced with the loss of transportation to visit the local prairie site to collect data (Plan A), I needed to pivot. Plan B was finding a database containing information about biodiversity in another ecosystem. I read about the vast number of species estimated to live in tropical rainforests. Maybe students could make comparisons between temperate and tropical ecosystems? I looked far and wide, even soliciting help from colleagues. Regrettably, after an extensive search and investing more time than I had, no suitable dataset was found!
Using What You Have
Time for Plan C. Realizing we couldn’t go to the site we visited in the past and lacking a suitable secondary dataset, I decided to use our own school grounds differently. Rather than comparing two distinct geographic ecosystems, students could make comparisons with data they collected from multiple sites across their own environment the school grounds.
Hadley: Biodiversity is the relationship between all the organisms and other stuff in the environment.
Teacher: That’s a great way to explain biodiversity. What exactly is the other stuff'”
Hadley: I think it includes air.
Margot: Yeah. It’s how hot or cold the air is, otherwise known as air temperature. Oh, maybe precipitation could be a factor, too.
Diego: I think ‘other stuff’ includes plants and trees. Wait a minute… those are organisms, right?”
Samara: I just thought of something. Other stuff isn’t alive, but it affects the stuff that is living.
Teacher: You’ve got it. We’re going to study biodiversity of organisms, the living things, here at school, as well as other things that are part of our schoolyard habitat.”
In preparation for kicking off Plan C, I presented our essential unit question, “What is the level of biodiversity on the school grounds?”
To start us off, I knew we had to get acquainted with our place in a new way. I downloaded a Google Map image of our school grounds, printed it, and divided it up into a grid of research sites Each coordinate site was marked by a flag so students could easily find them on the map. We have an amazing schoolyard which includes several natural and human-made features: rain gardens, an orchard, an effigy mound (a raised pile of earth in the shape of a bear and a line built by local indigenous people between 800-1000 A.D.) a multipurpose field, and about an acre of vegetable gardens. It had taken many years of working with many students to get it established. Learning to read and use the map was our first lesson. Students worked in small groups, similar to bingo where I called out a location on the map and students would tell me about a feature they could see or knew was found in that location.
Deciding where to explore
In the past, I had taken students outside and turned them loose. They explored anywhere and everywhere. Needless to say, it was a bit chaotic. I wanted to do a better job of managing things this year, so I assigned student groups to specific grid sample locations. Before we went outside, I wanted to hear their predictions about where we might find the most diversity and use that information to guide our learning.
Samara: Definitely not the effigy mound. We don’t want to walk a lot on that.
Margot: I really want to compare the mowed grass to that part. Like, near El to D3. That data would be way different! [I asked for them to elaborate] Cause, there’s way more people there. There’s gonna be way less diversity.
Diego: Yeah, we aren’t allowed to go anywhere near the greenhouse except when we are with a teacher, so I’m curious to go there. There’s a forest over there so there’s definitely gonna be lots of plants and animals.
Hadley: Umm… I don’t really know what grows around the far side of the campus. Like around the greenhouse or gardens.
Teacher: All right, we need to decide where to collect data, why don’t we take a vote? How would we do that? I wondered out loud.
Carmen: Let’s do it using dot stickers, you know, like we’ve done it before for other things. [lots of heads nodding]
Margot: Can we each get two votes this time … stick up dots on two of the squares?”
I started by asking students, where do you think we should collect or where would it make sense for us to collect data so we could learn the most about biodiversity? As a result, we made some decisions together about our data collection space. We would collect data at the grid locations listed in the table below and highlighted in gold on the aerial map.
Aerial image of school grounds with student research grids.
Gathering Data in the Field
I had loftier goals for my students this year in that I was eager to introduce them to complex data, with more than the three attributes (variables) like we had collected in the past… but it needed to be in a way that they could handle. In addition to using the schoolyard grid, they would collect data over a longer period of time- six different days enabling them to build strong ties to their sites. I asked students to observe, document, and quantify a much wider variety of species and record “other stuff” like the temperature and additional weather conditions for 13al attributes per location. | considered methods and protocols that could be used to calculate species richness. like quadrats and transects. I was torn. These methods would produce data to describe the biodiversity but it felt like the exploration and iov of outdoor observations might be lost with the protocols I found and I still had future classes that would return to the prairie so I didn’t want to change methods too much.
Managing Data Collection in the Real Teaching World
Before going outside, I shared a series of guidelines for exiting the building, collecting and recording data collaboratively, and treating organisms that were observed humanely. I had high hopes that the small, assigned site groups would reduce the amount of physical and verbal conflict amongst students and give me time to support students as they productively worked.
Best Laid Plans
For our first outing, I asked students to document every living thing they saw, similar to a nature journaling protocol we used in the past. This form was a simple data collection sheet and served as a trial run for noting discoveries. On this initial outing, we all went to one study site that I had subdivided. Each group collected data for a shortened session of 15 minutes. Group 1 and 5’s conversation
Group 1
“We want to catch a bee. But we don’t want to get stung! Maybe I could put a flower on the ground, and the bee will just come over to it. Then we could catch it real easy. That seems less risky to me.” I jogged over to them wanting to save my voice, “I want you to catch one, too, if that is what you want. Use the vial from your toolkit. Otherwise, your group could observe it. Remember, we don’t need to capture it.”
Group 5
“Oooh. I just found something big. I think it’s a cricket.” They went on to record their third organism. Before I moved on, I complimented them on their work and reminded them to “look for all different kinds of living things, not just things that move”.
I was pretty happy with what I saw and heard. Most kids were engaged in the collecting process. I heard a few screams, which was to be expected. There’s usually some drama with this class. I gave a one-minute warning and blew my whistle to signal the end of fifteen minutes. I wanted students to have a good first experience, given the conversation we had in the field and on the way coming back inside, I think they did. While we gathered back together in the classroom I highlighted the positive data collection and participation behaviors I observed and asked the students to share the number of organisms they found. The kids all shouted total numbers at once. I mentioned that I saw a few groups catching only one type of organism for the entire time and asked the class why we were outside.
I couldn’t have said it better myself!
The first round of data collection on paper was quite successful. Back in the classroom, it was time to enter the data into a spreadsheet. Looking back, I was absurdly confident that a group of middle school students could responsibly handle entering their individual data into one, shared spreadsheet. It took all of 30 seconds to realize some students were writing inappropriate messages in the cells instead of data. I quickly shut down the whole-group spreadsheet and posted a blank template into Google Classroom where each student entered their own data. I then copied and pasted all of their data into the same datasheet.
We looked at the dataset as a class. Students Identified plants, arthropods, mammals, and birds. In the future, they would gather data for each type of organism separately. I designed data collection sheets for each type of living thing.
Bird, Plant, and Insect Observations
Students focused on observing and recording data about birds on their second outing.
Interestingly, birds can be observed indirectly (presence of a feather or hearing a bird call) or directly (observed ). To prepare, students brainstormed birds they already knew. I then introduced other species that live in our area, and how to use field guides to find images and additional information. We were getting ready to head out, and kids were randomly chatting.
Hadley: I already know at least ten different kinds of birds! I know tons because I play Wingspan with my family. It’s a cool board game. It teaches you about birds from all over the world and their nests, eggs, food, and habitats. My favorite is the Little Blue Penguin.
Margot: My favorite bird is a cardinal. I like the male cuz it’s red. Male birds are more colorful than females.
Carmen: That’s not fair!!” a strong-minded girl exclaimed. “Is that even true?
Teacher: Let’s head outside and see if we find evidence to support or disprove that claim,” I suggested. I heard that some of you found and downloaded a birdwatching app last night. These are like field guides, I might use Merlin Bird ID for birds I don’t know, and if you have those apps, you can too.
Using phones in this way was incredibly positive. As a result, some students confidently informed me which birds they found. I still had to identify quite a few, but I’m getting better at letting kids use tools they have at their disposal to find and record their observations. It beats me doing most of the work!
I tried incorporating technology into this collection process by having students enter the data directly into their Chromebooks (using our school’s recently expanded Wi-Fi coverage). This would prevent them from having to collect the data on paper and then input the data. Unfortunately, some sites were located beyond the wifi range and managing computers in the field is less than ideal. At the end of the day, one of my energetic students, Carmen, asked “Why didn’t you just use a Google form, then we could use our phones?” She was right, but the idea hadn’t occurred to me.
On subsequent trips outside, students spent two days using paper handouts to collect data on plant specimens and arthropods. Given the high numbers of species in each of these categories, I provided more time for documenting data. This allowed students to slow down and look more carefully and closely for smaller, less obvious organisms. They had time to collect data and appreciate the beaut of the natural world in their schoolyard.
On subsequent trips outside, students spent two days using paper handouts to collect data on plant specimens and arthropods. Given the high numbers of species in each of these categories, I provided more time for documenting data. This allowed students to slow down and look more carefully and closely for smaller, less obvious organisms. They had time to collect data and appreciate the beaut of the natural world in their schoolyard.
Even though I had my share of problems to overcome and found myself moving from one plan to another, I was reminded that collecting primary data is powerful in many ways. I know I’II keep doing it however it looks.
Young birders at work.
Cleaning Data
The Hurdle of the Data Itself
Collecting data over multiple days and slowing down the process to look at plants, birds, and insects separately, really captivated my students. I wanted them to work with complex, messy data, but what we had created was too messy. In the past, for example, we simply compared the total number of plants at our school to the number of plants at the prairie. Now, we have many more attributes including weather conditions, vegetation height, color, and diversity of species.
How do I get all the data for all the organisms plants, birds, and insects–into one class datasheet? Was this even possible? For each observation day students collected data in the field using a datasheet unique to the organism they observed (see examples in Fig 1).
Fig: 1 Examples of data collection sheets used in the field
I was hoping I could cut and paste the tables together. It didn’t take me long to realize that in an effort to create unique protocols for each organism, I not only had different attributes (column titles), but I had also failed to list the attributes in the same order. When I looked across all of the days, I realized that the problem was bigger than I thought.
I wasn’t sure how to structure the dataset so students would be able to compare the different areas of our schoolyard. Should I list the grid locations on the left and have a different column for each species observation? I tried but discovered I didn’t have room for all the other data. Where would the weather data go? The date of collection? I tried merging and organizing the data from just two groups in a few different ways to see what made the most sense. I ended up with organism observation (what I called Type of Organism) on the left-most column. Then, for each column to the right, I put other attributes that were collected.
Even with the help of my teaching partner, it wasn’t feasible to clean up, copy, and enter all the data collected from six days of venturing outside. There were just too many data points. We used our energy to merge the plant data from all the classes I teach into one datasheet. We created drop-down menus to help reduce spelling errors and speed up the entry. We saved the file as .csv and uploaded it into the Common Online Data Analysis Platform (CODAP) so students could explore the next day.
Exploring Data
Provided some descriptive data questions to guide them
While we weren’t able to conduct a comparative study between two unique ecosystems this year, my students were able to explore the biodiversity on our own school grounds making comparisons using the data they collected. Before they looked at the data, we visited our Analysis Data poster and identified three different toes of sentence starters. I explained that the first set of starters (pink) might help to create a caption for an individual plot. The second set (gold) could be used to help compare things like two different locations, plant types, or even plots. The third set (teal), would help express things they were unsure of or curious about after using the data.
Class poster we use with Data
After students used their sentence starters, I gave them a chance to explore their data which had been imported into CODAP (Comon Online Data Analysis Program). My students had already been introduced to CODAP and had a little experience using it. We examined a couple of plots together as a whole group. I got our conversation started by displaying two plots that were commonly made by small groups and then saying:
“There are a few different ways we know our school campus. We have our experience from coming to school and spending every weekday here. We have a connection to the campus because we live close by-it’s in our neighborhood/city. We have spent time studying one particular area of our school grounds–in our grid locations–for 6 days. Finally, we have the data we collected. We can use all these ways of knowing and all the information we collected to help us describe biodiversity on our school campus. During our conversation, it will be important to share whether you are using the data plots, your personal experience, knowledge from another source (like our textbook or gardening), or a combination of things to inform your answer. Let’s start. All seventh-grade science classes predicted grid Al was the most diverse. Did our experience and data align with this prediction?”
Carmen: My plot is the best, C3 and it almost had the most plants, so it has high diversity. I’m using the plot. Look at that high point [pointing to the high value on Fig.1]
Teacher: So based on the data and your first-hand experience, you would say C3 is high in biodiversity. Looking at our plots, does anyone have similar or different thoughts?
Diego: I just thought of something. Other stuff isn’t alive, but it affects the stuff that is living.
Teacher: You’ve got it. We’re going to study biodiversity of organisms, the living things, here at school, and they are impacted by other things like water or human activity. Right now with this data we are looking at the amount of different plant types in an area.
Hadley: Wait, how can that be? [Pausing and looking at the poster]? I wonder…..that’s mostly shrubs [pointing to map]. Forests should have more life and there aren’t trees there?
Teacher: Can someone from C3 give us some information from their experience there?
Diego: No, wait. We were at C3. There were mostly shrubs and there were mushrooms everywhere. No trees.
Teacher: Hmmm, look we can see that there is a value for fungi on our Plant Type plot for C3 [pointing to Fig. 1]. Thinking about our introduction to ecosystems, should fungus even be in this plot?
Carmen: They don’t do synthesis [photosynthesis]. They eat dead stuff like old wood. They’re important but not plants.
Teacher: Okay, so if we eliminate the fungi [demonstrating how to hide values on the plot in CODAP] from the plant category, how would we answer the question, which section is the most and least diverse? Talk with your table groups. Be sure to use evidence from one or both of the plots
Margot: Study site B2 had the most diversity. It had the most plants, the number is the biggest.
Samara: Study site B2 had 37 different species.
Teacher: I wonder why B2 had the most plants. I am also wondering about Diego’s question about whether trees always mean more biodiversity.
Teacher: One step in analyzing data is to look at the highest and lowest values. have made a plot with the two highest and lowest counts to help us focus on our question (see below). If you are stuck, try using some of our sentence frames.
Diego: B2 had 37 compared to study site C2 which only had 32 different species. But I say B2 isn’t the most natural. B2 is the greenhouse and is there because of the garden club. Counting plants there doesn’t seem fair. C2 is more natural.
Samara: I’m surprised, I thought areas with trees would have the most plants and be the most diverse. C2 has no trees. Cl and D3 have trees and they were the lowest. This makes no sense.
Carmen: I’m surprised there was so much stuff there in C3. It wasn’t fair we had to count forever. The trees had a lot of insects, but we don’t have that data. If we looked at all the living things it would be more fair.
I realized through this experience that students didn’t need to use all the data they collected on the school grounds to have a meaningful data exploration. Students are able to use the data to begin describing the richness of plant species and describing the frequency of plant types by location. I wasn’t able to provide an accurate total for each type of organism observed by students in a timely manner and students couldn’t make inferences like whether certain types of plants increased the presence of birds or mammals. Still, I used the opportunity the next day to have students apply their 6th grade math skills by analyzing box and whisker plots created for the Plant Types (See Fig. Xx). Students had a chance to describe the variability of plant types (ie., trees, shrubs, and forbs) laying the foundation for a deeper understanding of biodiversity on our campus. Students were able to use their observations and plant name from the dataset to recognize that some plants were more common than others. I was invigorated, while feeling disappointed at the same time. (For more about reading Box and Whisker Plots see reference notes).
Next Steps
I am happy that my students could manage being in the field for so many days and were still curious. They learned about their campus in a whole new way and posed questions I am hoping we can come back to over the year. They also had their first experience with making plots in CODAP. The students and I learned that combining data into a shared dataset is challenging. lam hoping that we can continue to collect data together through one of NASA’s Globe Campaign and their shared protocol might help us avoid some of these challenges and dig deeper into the data. I am hoping students will be better prepared for their culminating end-of-year project in which they would design, collect, and present their own independent research.
While I’m glad we were able to expand our school-based data collection and research study this year, my wheels are already turning in regard to making improvements in the future. At the very least, I want to improve data entry and reduce the time needed to do it. I want to help students collect data that helps them compare across sites in a quantitative way through transects or quadrats. I have learned a lot through this experience, but I know I still have much more to learn (see our tips for data collection in the classroom).
I will continue to offer my students opportunities to build excitement about what they learn and do in science. I will share my passion for the outdoors and provide my students with authentic experiences to gain a greater appreciation for their place in the world
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