For one month, students collected data about themselves. As a group, they collected data on the number of hours slept each night and the amount of pages read during a certain time period. In addition, students had one to three choice items to collect data on. These choice items were fully open to whatever a student was interested in learning about. Some examples of choice items include amount of video gaming, minutes of violin practiced, physical activity, body weight and more. This mini-project was part of our first unit of the year, called Project Big Data.
A student comment during reflection:
“… my average number of pages read per minute was 2.42 when I am supposed to read only 0.75 pages per minute. This shows that the book I was reading was at a lower level than me.” ~EW
Inspiration for this project came from Dan Meyer in his posts on dy/dan: The Feltron Project and The Feltron Project: Post Mortem. Dan Meyer also had an interview with Nicholas Felton about data collection.
Project Big Data driving question: How do we use data to describe and improve ourselves, our community and our world?
As part of the Big Data project, the “Feltron Project” focused on ourselves. The general project flow was as follows and is captured in this slide deck:
- Introduce Michael Felton and his work in describing himself.
- Launch the idea of collecting data on sleep, reading and a choice(s) for the following month.
- Collect data with completion check-ins
- Summarize Data
- Use the https://technology.cpm.org/general/stats/ site to create box plots and histograms of the data.
- Analyze data
- Construct explanations based upon questions for each category (sleep, reading…)
What went well?
- Looking back on analysis from students, it seemed like many gained insight on some of their habits.
- I was curious to see that the sleep data was a lot better than I had been expecting. Sure, there are some averaging 7 hours or less but the majority were at 8.5 hours or more.
- Reading rates provided interesting topics of discussion as some were surprised to find that they are zooming through books. Too easy?
- Students began developing a better appreciation about data with a project that relates them.
- “I am proud of finishing the feltron data collection because i don’t like recording stuff and i stopped reading in 4th grade because we were required to record it (and i just didn’t record).”
- “I am proud of trying to learn more about myself, such as how many hours I sleep and how much I exercise each day, because I usually don’t keep track and don’t really care about my own well-being so I think it was nice that I tried to keep track of my hours of sleep and exercise etc.”
- “I wouldn’t necessarily say I’m proud of this but because of the Feltron data collection I learned that I don’t read that often and now knowing that I would like to change and fix this.”
- hmmm….”I don’t really like tracking my life for 4 weeks. I don’t want to track my daily life because I find it very scary.”
What could use a good dose of revision?
- A stats meltdown – In mathematics, I restructured the order of units to begin with statistics. Unfortunately, this seemed to be more than the students were ready for and after a few weeks, my co-teacher and I decided to switch content focus to rational numbers. As such the project lost some of its grounding.
- The work flow was not well scaffolded. I had hoped that the synthesis at the end would not take students a lot of time, but it did. Students data collection should make sure that they are processing information as they collect it. For example, we wound up turning time into decimal representations. This could have been done while data was being collected. Reading rates (pages / min) could also have been precalculated.
- Time ran out in the end and there was not a solid work session of modeling the process from strong data analysis to explanation. This is essential!
- Data analysis was quite strong and centered on supporting a claim for some students. Many others had superficial connections. Is this OK if it was one of the first times students worked with data or is it important to push for stronger work this early in the year?
- More check-ins. I really enjoyed the time to talk individually with students about their work on this project. The conversations often explored a bit of their personal lives so I learned more about my students. The check-ins also helped to motivate students in sticking with the project. Unfortunately, a few students slipped through the cracks and did not have data at the end.
- Rework focus and ground in operations with rational numbers. The data collection about self was a nice start.
- Time for discussions along the way that examine evidence and how data can be discussed is important.