Hi Josephine!

This topic is right up my alley! This year I've been using activities from Skew the Script and from the book High School Mathematics Lessons to Explore, Understand, and Respond to Social Injustice by Berry, Conway, Lawler, and Staley in my community college statistics classes. I've liked the diversity of topics I have at my disposal from these two sources. What I really like from the HS Lessons book is the focus on empowering students to DO something about the inequality they see. 

I've used CODAP before. How are students taught CODAP? Were they taught in classes before the pandemic? How have you, or have you, modified your modules due to how schooling has changed due to the pandemic?

I teach strictly online (not remote) so getting students to have a robust conversation is a challenge. I've turned to using Google Jamboards as an easy way to share ideas (it beats scrolling a discussion board!), but there's not much back-and-forth conversation. I'm not sure how to fix that. 

Hi Jennifer,

Thanks very much for your interest, comments, and questions! It is great that you've been using lessons from Skew the Script and Berry et al.'s book. Our work is very much in the same spirit, and was inspired by the earlier writings of Lawrence Lesser and Eric Gutstein (and Gutstein's colleagues). Our team knows how much time it takes to identify compelling questions that relate to students' lives, and find datasets that can help students explore these questions. AND build guided investigations that both allow data exploration and provide sufficient support so students can reach learning goals. Our team has loved working with teachers to develop and test these types of data-focused learning experiences.

In our modules, we provide written tips and guides to help students learn the CODAP tools they need to explore the driving questions of each lesson. But we found during our pre-Covid in-person iterations that many students preferred having the teacher demonstrate in class how to use relevant CODAP features. After high schools went remote/hybrid, teachers and students continued to find it most efficient to learn CODAP tools through teacher demonstrations, accompanied by our written guides on the side.

Hats off to you for teaching fully online and working hard to promote strong student discussion in this format. We tested one module with teachers and students in person pre-Covid, and the same module (slightly streamlined) with teachers and students in a hybrid format during the pandemic. We haven't yet analyzed our data to compare the two implementations fully. But we can tell from our classroom observations and initial teacher reports that the level of student discussion was much, much higher when students were in person. Teachers reported that it was very hard to get students to talk to each other in breakout rooms.

However, we have started to notice that when students were remote, their written responses to lesson assignments often seemed more thoughtful and detailed compared to when students were in class together. We are wondering if for some students, the pandemic prompted deeper reflection. I wonder if in online learning settings, when students are typically learning more independently, if there are ways to promote deeper student dialogue within themselves or with one other person (like the teacher or another classmate). But here I'm just speculating, and brewing new research ideas... =)

Hi Jacob,

Thanks for watching our video and visiting our site! It is great to meet other researchers and educators who are working to promote data literacy among students by having them explore and investigate real-world, relevant issues with large-scale data.

Yes, we specifically sought to use person-level microdata in our project for a couple reasons. For one, we come to the project with the hypothesis that students will better relate to data they have not collected themselves if they can see individuals and their attributes in the datasets they use.

Second, one of our research goals is to promote and support students' multivariable thinking -- that is, giving students opportunities to explore and make sense of confounding and interaction effects when working with more than two variables. This is a skill that statistics educators have noted is critical for working with big, real data, and has not been emphasized in K-12 curricula. The most recent Guidelines for Assessment and Instruction in Statistics Education (GAISE II) report highlights how this type of thinking should be introduced before college. By allowing students to work with person-level data, we have them explore questions such as: What is the gap in incomes between males and females in the U.S.? How does this gap change (and does it even go away) when controlling for education, or region, or part-time/full-time work status?

Our ultimate data sources are the U.S. decennial census and the annual American Community Survey, and we accessed person-level data through IPUMS-USA from the University of Minnesota. Our wonderful CODAP partners at The Concord Consortium built a plug-in tool into CODAP that now allows anyone in the public to access person-level micro-data from these sources going as far back as 1850 to 2017. Our project selected a large set of person-level attributes that students can explore. And our CODAP partners worked with the IPUMS folks to figure out how to deal with sample weighting, so people and students who download extracts from the portal don't have to deal with sample weights, and they can know that each person in their dataset counts as a single person.

As you can see, I love talking about this work, so feel free to ask more questions if you have them. And if I can't answer, I'll direct you to one of my brilliant team members who most likely can!

This is a very helpful explanation. Thank you, Josephine!

Hi Marcia,

Thanks for your comment, and visiting our site! We would love to work with higher ed faculty in four-year and two-year institutions who may be interested in these types of materials. Two members of our team are statistics faculty at Cal Poly, and while I'll let them speak for themselves, they have have been exploring some of these datasets and and ideas with their undergraduate students. 

We know that there have been many efforts in the U.S. and across the world among statistics educators, particularly in higher ed, to bring real data and real issues into the classroom. We are connected with the ProCivicsStats project in Europe, which will be publishing a book from Springer later this year on datasets and lesson ideas they have developed to promote civic statistics across the world. Centering statistics and data science education around real-world socioeconomic and policy issues makes the learning meaningful and reaches students who may not, for a variety of reasons, see themselves as "data" or "numbers" people. Our early research suggests that this approach can help change students' views of themselves and their interests in working with data.

Hi Josephine,

Thanks for your response. I'm also interested in using social justice data as a means to connect Statistics majors with the wider world and the impact that they can have on societal issues through their work in statistics.

Hi Marcia,

Totally agree with you on the value of using the social justice context to help Statistics majors (and minors, and pretty much all college students) see how relevant statistics and data skills are to understanding the world around them. I am a statistics faculty member at Cal Poly, SLO, and have used some of these contexts in my intro stats classes. On the end-of-term surveys students often report the wage gap explorations as ones that made the biggest impressions. We hope to develop more such lessons and modules, and use them at the college level - both with majors and non-majors. 

- Soma

Hi Soma,

If you have any materials that would be good for use in a regression/analysis of variance course, I'd be very happy to try them out!

Hi Jan,

Thank you for checking out our video! Thanks for asking about our interdisciplinary collaboration efforts. In the first year of our project we worked with 5 mathematics/statistics teachers and 5 social studies teachers, (mostly) paired from the same high schools, to help us develop our "alpha" version of our two modules. It is important to note that none of them co-taught together -- either before or after joining our project. However, their department heads were supportive of them collaborating as part of our project, and they worked together to provide feedback and learn to use our materials. The cross-disciplinary collaboration that we observed happened mostly during our PD/materials development sessions, when mathematics teachers supported social studies teachers as they learned to explore data in CODAP together, and when social studies teachers provided us with ideas on driving questions to anchor lessons and ways to support conversations about difficult social justice issues.

By design, our materials were tailored primarily for use in non-AP mathematics or statistics classes, and based on our early testing, we found that to have any chance of boosting student learning of core statistics and data concepts, we needed to tailor our supports and materials for this context. Largely due to this focus, only two social studies teachers felt they could teach one of our modules (the one on immigration to the U.S.) in their social studies classes. One of these teachers used the module largely as-is. She observed her partner statistics teacher using the module before she launched it herself, and the two may have consulted on implementation strategies (they were teaching different grade levels and different students). Another teacher modified the lessons greatly because the heavy quantitative emphasis in the materials didn't align with his teaching goals.

Our project couldn't break down departmental silos in schools themselves, but we provided teachers from different departments within schools opportunities to come and talk together about common learning goals and strategies that cross disciplines. In our future work, we would love to work more in this space, and especially to see what is possible in supporting more quantitative thinking within social studies learning.

Hi Josephine,

Cool project! Thanks for sharing your video.

We found that CODAP was a real concern for our social studies teachers. They felt that it was too complicated for the few graphs that social studies teachers will use in a give semester -- the return on investment wasn't high enough.  We had a paper at SITE 2021 on this story, which I described in this blog post.

Hi Mark,

Thanks for watching our video! It's very interesting what you've been finding with social studies teachers. When we began developing our materials, we worked with paired mathematics and social studies teachers, and the latter were all interested in bringing in more quantitative data analysis into their courses. Both sets of teachers had a small learning curve with CODAP (many mathematics teachers have never worked with data!), but both sets of teachers ultimately found CODAP easy and fun to use to explore data.

It is true that in our initial iteration of classroom testing of our materials, only one social studies teacher implemented one module fully -- but we think this was largely because our project goals are to promote statistical thinking and data analysis practices within non-AP mathematics classes, so the focus of our materials is more quantitative than most social studies teachers will feel is aligned with their curriculum goals. But as we explore bringing our work to more social studies teachers, we will continue to start with the social issues and topics that are aligned with social studies standards and courses and help bring quantitative skills and tools to bear to understand the issues. We don't focus heavily on computational thinking skills or programming -- instead we focus on the overlap of the 4-step statistical data investigation process with the 4-step social studies Inquiry Arc and support teachers and students who want to use quantitative data and statistical thinking in their history (or economics or civics) investigations. We've been exploring these ideas with teachers in Massachusetts and there is interest -- although we'll need to find out how far the interest goes!

Andee-- We have been so lucky to have you serve as the chair of our advisory board, and we have learned so much from you throughout our project. 

For our third module we always wanted to bring in real data and a compelling social justice context to have students explore associations among quantitative variables, i.e., bring in the concepts of correlation and linear regression when looking at two variables, and then examine interaction effects with a third variable. The ACS and decennial census data didn't provide us with many person-level variables that are both quantitative and set up compelling social justice questions (e.g., how income varies by age and by other third variables might be of interest to some, but there aren't many more quantitative variables to choose from).

We therefore started to explore person-level health data that are publicly available, but it is interesting that many health variables in the datasets we looked at are categorical rather than quantitative (e.g., more variables indicating incidence of health conditions rather than levels of specific conditions). We also had to stop pursuing a third module due to COVID disruptions and the need to pivot to helping our teachers test our materials in remote/hybrid environments.

In the future, we may need to move away from person-level data in order to explore associations among quantitative variables with authentic social justice questions. Some ideas include looking at the neighborhood or census tract as the unit of analysis, so we can explore associations between poverty levels and area racial composition, for example, or housing prices by percentage of immigrants in the population. But as you know, working with rates is hard for students. This is an area prime for more exploration and research -- because these issues are real and meaningful for all of us!

Hi Laura,

Thanks for your interest, and your question! Our modules, designed for high school grade levels (primarily 12th grade), expect that students will have been exposed to statistics and data concepts addressed in 6th through 8th-grade standards from the Common Core State Standards for Mathematics. However, we have found that students in the classes we have been serving don't necessarily have a deep understanding of these concepts. So our materials help to deepen (and sometimes re-build) students' understanding of these concepts through our applied data investigations. Our materials can also be used by teachers to help students learn concepts targeted in the high school mathematics standards (e.g., conditional proportions).

For example, students develop a stronger understanding of the difference between the mean and median and how they are (or are not) affected by skewed data (as seen in U.S. incomes). They deepen and/or build an understanding of conditional proportions by predicting and then investigating, for example, the region of the U.S. with the highest percentage of people who are immigrants, versus the region of the U.S. where the highest percentage of immigrants have settled.

We don't expect students to come with specific prior content knowledge about the social studies content of our modules. Instead, we provide online resources and handouts to support students' understanding of and interpretations of their data findings. But we hope that if students have already studied U.S. immigration history in their U.S. history class, for example, then our materials will give them an opportunity apply that knowledge to their data interpretations.

It's exciting that your school may be interested in promoting more interdisciplinary studies. In at least two of the high schools we've worked with, the principals and the teachers had either already moved or were trying to move their curricula in this direction. A principal at one of our collaborating schools observed students giving presentations on their final data projects from one of our modules and was excited by the possibilities of using the project as a model for a senior capstone activity. But we know how hard it is to build interdisciplinary collaboration in high school settings. Are you aware of a prior NSF-funded project, called Thinking with Data, that was led about 10 years ago by Phil Vahey at SRI? They built an 8-week curriculum involving social studies, mathematics, science, and ELA teachers in middle school focused on a shared environmental theme. Their findings about their successes and challenges might be helpful and informative for you.

Hi Lauren,

Thanks for checking out our video! I just checked out your video, and the work you are doing for your ITEST project looks very exciting and important. As a team, we have thought about how valuable it would be for students using our modules to interact with data scientists who look like them -- just as you do in your project. This is something we are contemplating for future work. =) If you have specific questions about our project we'd be happy to answer.

Hi Ashley - Thanks for viewing our video and for your comments! I took a quick peek at yours and it's exciting to see how you've been working with high school students to give them real research experiences. Our spirits are aligned! 

Yes, we worked hard to make U.S. census and ACS data accessible for students, and CODAP tools are very student-friendly (with a low threshold and high ceiling for data exploration possibilities). A comment that one student gave us in a post-module survey was how the module helped them feel like a real analyst doing the work that real statisticians do.

In each of our modules, we provide sequenced lessons that build students' comfort with using CODAP and conducting data investigations (moving through the four steps of the data investigation process). By the end of the module, they can more independently conduct a final data investigation that explores in greater depth a question of their own choosing -- either about income inequality among different social groups, or a claim about immigrants.

Hi Liandra-- Thanks for viewing our video, and for your comments! (I just viewed your project video and was inspired, by the way!)

I have to admit that I myself was never interested in statistics until I went to grad school to learn about social and policy issues that I cared about, and then learned statistics to better understand and analyze these issues. Many of the issues I cared (and still greatly care) about deal with race, socioeconomic inequality, and immigration -- given my own background as a visible minority and an immigrant myself. Knowing that adolescence is a critical time of identity development, it made sense to ask: Wouldn't students in high school be interested in looking at data that gives them information about themselves and their families and communities within broader U.S. society? Particularly if you're from a group that has historically experienced differential (and unequal) treatment? This was a motivation and hypothesis driving our project: Can we hook broader student populations and draw them toward statistical and data science work, by tapping into natural interests and concerns about their own places and opportunities within society?

Thank you! We both felt inspired after viewing each other's videos!

But wow - yes. All of these questions are spot on. You all have inspired me to revisit quantitative research because of the questions we can answer and areas of interest we can shed light on through statistics. Feel free to keep in touch! lalarsen@cougarnet.uh.edu

Thanks for visiting our site and for your great questions! When we first began developing our materials, we worked with both mathematics and social studies teachers to think about what types of social action students might want to take in response to the issues they were uncovering, and what types of civic activities teachers would want to support students in pursuing. Many of our social studies teacher collaborators were already conducting lessons with social action plans as part of their regular curriculum and student learning goals. Example activities that they described included students writing letters to local Congress representatives, as well as students researching and evaluating social change efforts launched by local community organizations.

Because we focused our module testing in mathematics and statistics classroom contexts, we followed the lead of partner teachers in these spaces. Although several of these teachers expressed interest in supporting students to follow their data investigations with civic action, none of them had the space or time to pursue these activities. Some mathematics teachers admitted that they needed more support in facilitating conversations around what can be challenging conversations about social issues in their classrooms. We provide resources from a variety of well-respected organizations on how to set classroom norms and facilitate these types of conversations, but this is an area that deserves its own dedicated focus. We are still very interested in working with teachers and in settings where there is flexibility in the curriculum to encourage interdisciplinary data projects that include civic-oriented action plans as a final component.

Thanks, Bridina, for your question! (I think I failed earlier to reply directly to you, so I'm reposting my earlier response.) These are great ideas. We've been focused most on possibilities for integrating our modules in high school social studies classes so we haven't been thinking quite as much of science classes. But there are certainly many topics that could lend themselves well to investigation in public health or earth science classes, just to name a couple of contexts (e.g., examining disparities in health care outcomes by race and income, or the unequal impacts of climate change on community living conditions and other environmental justice issues). There are so many possibilities, which I'll bet other groups in the current and past showcases have already been exploring (and I hope to carve out time to find them!).

Hi James, (I think I failed to reply directly to you in my earlier response, so I'm reposting here)

Thanks so much for viewing our video and connecting with us! It would be great to get together and talk. Just to let you know, a couple of us on this project work on another data literacy project, also funded by NSF, through its ITEST program. It's called WeatherX, and you can find more information about this project both at http://stelar.edc.org/projects/22767/profile/understanding-weather-extremes-big-data-inspiring-rural-youth-data-science as well as through http://oceansofdata.org/k16-projects. Anne Gold, one of your CLEAN collaborators, is an advisor for WeatherX! We aim to have a video for this project next year.

As we shared in our current video, the Strengthening Data Literacy across the Curriculum (SDLC) project has been serving high school students from historically marginalized groups (primarily Blacks and Latinos/as) and explicitly incorporates questions about social and economic inequality in the U.S. for students to investigate with data.  In contrast, our WeatherX project focuses on building data analysis practices and career interests in data science among rural middle school students with learning experiences that involve investigation of local extreme weather events. Using CODAP, students analyze current and historical data from one of our partners, the Mount Washington Observatory, as well as NOAA/the NCEI. Although we have not incorporated a social justice angle into current WeatherX curriculum units in the same way that we have done for the SDLC project, your comments encourage us to move in this direction as we think about how to develop our work further. If you have datasets that would allow students to examine disparate impacts of climate change and extreme weather on different communities (especially in rural areas of the Northeast), we would love to collaborate!

Josephine,

I will definitely follow up.  Connecting. And exploring the possibilities with WeatherX.  I'll be sure to check in with the ever incredible Anne Gold.  I am noting all.

Thank you!

Kristen -- thanks for watching our video and for your encouraging words!  As we do our research, I try to ask myself the sharp yet supportive questions that you, folks at Horizon Research, and other great researchers like you might ask us to keep us on our toes! =) 

Hi David,

Thanks so much for visiting our site, your supportive comments, and your interesting questions. We are aware of growing interest around the country about mathematics pathways through high school that provide alternatives to the traditional algebra/geometry-->calculus trajectory. In fact, we found great interest in our materials in Massachusetts among high school math department heads and teachers developing options for students in grade 12 who must take a fourth year of mathematics but are not interested in or on track to take calculus or AP statistics. We have also heard from mathematics teachers and department heads in the Boston area who wish to teach data analysis and statistics concepts in 9th and 10th grades in ways that make the learning relevant to students' lives and build understanding of social justice issues.

We have not yet tried to reach out more widely to geographic regions beyond the Boston region (where we have focused our early-stage project's development and testing efforts), nor have we (yet) connected with other projects or organizations that are working systematically on alternative mathematics pathways in high school. But we are very interested in making these connections, and would welcome ideas for promising contacts!

Thanks Josephine.  The Dana Center in partnership with CBMS has a project that engages a number of states that are looking at the common pathway leading to a range of courses to assist students in future endeavors.  I also work with a project in Virginia - Virginia Mathematics Pathway Initiative (VMPI) and this includes a stats option.  Feel free to reach out ot me at dbarnes@nctm.org if you would like to connect with the group working at that level.

Thanks, David -- this is very helpful information!

Thanks for your question, Jena! We begin each of our modules with an early lesson in which students critically examine our primary data sources - the U.S. decennial census and the American Community Survey. They read about their history, how they are collected, and importantly - they do activities where they examine the survey questions themselves and consider how easy or hard it would be to answer different questions. Students discuss what would happen to the data and the conclusions people can draw if people don't respond honestly, or if they don't feel comfortable answering and therefore generate missing data (e.g., how comfortable are people reporting their incomes? how comfortable are immigrants sharing any information with people they don't know?). In addition, a very important discussion early in each module is when students discuss what kinds of questions can be answered by data and what kinds of questions cannot. We feel these are fundamental elements of building data literacy, before students begin assembling their data extracts, choosing variables, and analyzing data to address the driving questions of each data investigation.

Hi Heidi,

Thanks for watching our video! Very glad you asked about our microdata portal to U.S. Census and ACS data, because it's available to the public right now! Anyone can go to https://codap.concord.org/, explore the page and existing datasets or go right to "Try CODAP," and in the upper left toolbar, you'll find an icon for "Plugins." You can then select "Microdata Portal" and it will bring you to the portal that The Concord Consortium designed for our project (but is available to the world). Through this plugin you can create data extracts from the decennial census or the ACS, using data from select decades and years from 1850-2017. Our project developed a detailed data codebook for students, but general variable/attribute definitions are also available directly within the portal.

Because ours is an early-stage research and development project, we have focused primarily on studying and refining our materials and student learning and interest, rather than creating products for mass distribution. But people have been reaching out to us and we are happy to help. Our goals for the future are to develop more materials, test for true efficacy, and to explore more widespread scaling. We are in the final year of our project so we are definitely thinking about next steps!