Hi Laura,

Sounds like you are already doing it!...starting with real data, letting students ask their own questions and teaching anything needed to answer their questions. That's great! Other high school classrooms have taken this well (Perry High School, OH, Scarsdale High School, NY and others). There is not much of a difference except going a bit further into inferential statistics at the college level. For high school boot camps we stay largely in descriptive statistics only because of the short time that we have with them. Flipped classroom works well pretty much across the board. Feel free to check out our videos on the website https://passiondrivenstatistics.com/. Post pandemic I anticipate more students will prefer the flexibility of video lectures. I am not familiar with many formal "approval" processes but agree this is an ideal curriculum for high school to college pathways. Currently passion-driven statistics is being implemented as a research methods course, a data science course, a capstone experience, and a summer research boot camp with students from a wide variety of academic settings (it is even used in medical schools!). I am currently working on shorter data-driven projects to try to get more data into traditional Gen Ed experiences. Here is our new website, https://digital-intro.com/. Happy to connect if we can be helpful to you in any way! ldierker@wesleyan.edu. 

Hi Lisa-

If your summer boot camp focuses primarily on descriptive statistics, I could totally see these units (or similar ones) being used in middle school where students are introduced to descriptive stats. Are you familiar with Jo Boaler's new Explorations in Data Science Course? I know it recently received UC a-g accreditation and will be piloted next fall.  I'm not  following closely but there seems to be similar focus.

https://www.youcubed.org/wp-content/uploads/202...

Thanks so much for sharing this with me! I was not familiar with the UC a-g accreditation mechanism so I will definitely be reading more about it. Thanks too for the Exploration in Data Science Course curriculum. It looks like they collect their own data, but is otherwise similar at the exploration steps. That is the wonderful thing about data, from novice to expert, the exploratory process is the same and it is one everyone can connect with. 

Though we have worked with students as young as rising 9^th graders but not 7^th and 8th, this summer, Kristin Flaming will be running a middle school teacher boot camp workshop in Oklahoma. Part of the SAGE STEAM Camp initiative, the goal is to expose girls from rural communities to STEAM content. The workshop will help middle school teachers incorporate STEAM in their classroom. We are excited about the possibilities!

If you know middle school or high school teachers interested in adding data driven projects to their courses, we are also holding a short virtual workshop as part of the USCOTS workshop in June. 

https://www.causeweb.org/cause/uscots/uscots21/workshop/6. It will be held on Thursday, June 24^th and Friday, June 25^th 4:00 pm – 6:00 pm ET.  All are welcome! 

Hi David, There are a wide range of data sets and questions and the sky is the limit... Is exposure to a drug use prevention curriculum associated with lower rates of experimentation with substances? Are religious adolescents less likely to be depressed? What factors predict ‘safe sex’ practices? Popular data sets includes ADDHealth, National Household Survey of Drug Use and Health, General Social Survey, Outlook on Life Survey, among others. We have even used a data set on Mars craters. A very good sources is ICPSR from the University of Michigan. We have also partnered with local non profits and school systems who are able to deidentify their data appropriately. We are always looking for more data sets! Lisa

Thanks Lisa!  The asking real questions and using real data is really powerful!

Thanks Bridina for the question. We have found the best way to teach the teacher is by having them attend a workshop with us where we have them complete a small project much like their students will complete on a larger scale. This allows them to experience the process start to finish. We find they are more comfortable with flipped approach, have a better understanding of what their students will do and their needs. 

Hi Bridina, Just to add to Kristin's message... for very motivated instructors who see the benefit and have some experience with a statistical software platform, support through a workshop has definitely worked. That said, we are missing so many because of the PD needs you are talking about. What is needed is far more  intensive and supportive than a workshop. At Wesleyan, we have instructors support the course as a co-instructor the first time out. They can just jump in and talk to students, or work on their own short project to improve their skills, or usually a combination of the two. No instructor has ever left this experience not completely hooked on the model and with a huge infusion of confidence. Put simply the instructors need to be students in a project-based course first to feel both the excitement of working on their own question and having the opportunity to hone their statistical software skills. People are too busy to do that training outside of the work day. I am convinced that bringing PD into the classroom is the answer. And it does not have to be expensive. If I have 20 students in my class, I would be able to take 35 or more with a co-instructor even though that co-instructor is in the learning phase. Project-based learning is all about keeping the conversation going. Everyone that is part of that conversation is helping (including peers!). 

While our model has had loads of success in psychology stat courses, sociology, biology, political science, etc., we have found that most Math teachers have not been exposed to applied data projects and/or statistical software. They can pick up these skills very, very quickly with a co-instructor that already has them! Workshops are not enough. 

Sherry, Thanks so much for sharing that paper. I love the idea of calling them "data moves". Its perfect and since data management is at least 80% of any data project (something that always surprising students), the moves are not only central to a project but also arguably the most empowering piece we are giving students. I mean you can look up how to do an ANOVA if you forget, but the decision making process that helps you manage your variables is a central skill that needs to be used flexibly and with insight. We teach data management early (no later than week 3) and then students keep using those skills throughout the semester. Here is a link to the "chapter" that outlines many of the moves we want students to consider (along with code in all the major stat packages to make them happen). https://ldierker1.github.io/passiondrivenstatis.... The accompanying video links (one for each software platform) walk students through how decisions were made, what the cleaned up variables look like and how they might be used. We don't tell students how to manage their data, but we help them make their own decisions and then give them support to implement those decisions. Students go back to the data management ideas again and again as they choose new variables for their project and deepen their research questions!

Thank you Israel. We take a student-centered approach to the course. We also use the frame of mind when working with an instructor new to the approach, new to working with real data, etc. in that we meet them where they are at and work forward. For those interested in learning more we offer workshops but we also do one-on-one support via Zoom and email. Instructors that are less comfortable with the software we try to Zoom into their course during data management to help support them the first time through if we cannot be on campus.