Prework Readings and Reflection Questions

We have assigned some readings to help start our day and our thinking about student learning and working with data. You can access those readings here:

After reading, please reflect on these questions:

    What are important skills and understandings for students to develop around data? Why are they important?
    Which of these are students working on in your class?
    Which of these would you like them to work on?
    How can you imagine working with other teachers in your team or school?

Please share your reflections here.


our focus has been primarily on the following :
When investigating a question, make sure you collect the appropriate data to do that.
Carefully thought out data sheets ease analysis considerably
Variation in data is can be where the really good stuff is (things we may not have thought about)
How to present data is a way that better reveals patterns
How to accurately use data to support conclusions
Introduction to the myriad, and creative ways, people present data. And how to approach it for understanding. What works? What doesn't?
Conclusions are on,y as good as the data that goes into it. Understanding how a study was done, by who, is critical. Just because there is a number attached to something, it doesn't necessarily mean anything.

I'd like help organizing and having kids analyze bigger data sets (vital signs, ebird, etc)
I have not gotten into what I think of as statistics with my class, so I'd love to learn how to bring this to fifth sixth graders, and what level is appropriate.

Also as addressed in the Maone article, students need to develop not only an understanding of central tendency but also the ability to take it one step further look for variability. This requires students to look beyond just surface level understanding but really thinking about the data and making conclusions about what it means.

This is my first year teaching science and we have not done much work yet with data. Our mathematics curriculum coverage of data and statistics is lacking student engagement and is near the end of the year so there is not a lot of time left to really do it right. I am working on improving the quality of the content and looking for ways for students to feel invested in the data they use to explore the mathematical topics.

In my school I am the math and science department. I feel through that there may be opportunities for us to work and collaborate with other schools to increase the quantity and validity of data.

It is important for students to collect relevant data or good samplings so that their analyzation is valid. Students should learn how to represent this data in order to communicate with others clearly. They use mathematical models to analyze the data and come to conclusions, make predictions and/or learn from the past.

My students are working with mathematical models. I would like them to start collecting data, graph it work with technology looking for mathematical models that might fit it.

I would like to use data that other teachers gather or share data.

Technically speaking:
My students will use models to analyze data. They will also use mathematical, computational, and/or algorithmic representations of phenomena. They will also apply techniques of algebra and functions to represent and solve scientific and engineering problems. At least this is what I conclude from the reading.

It is important that students understand how to collect and interpret data and to look beyond the central tendency of the data. the variability of the data collected . Students need to be able to represent data that are free of bias or misinterpretation. By exploring the variability of data (beyond the central tendency) may shed light on a new discovery or new direction for further research. Students are learning to differentiate between dependent and independent variables, and control within in an experiment. Data collected is examined mostly by central tendency, but outlier data is a point for discussion.
I would like to start spending more time examining the variability of the data with my students as this is often written off as "outlier" and inconsequential by most students. .
I think it would be helpful to work more collaboratively with data among our team of teachers. If we shared data among teams there would be much more data to work with adding validity to our numbers. Also a richer sample of data may reveal more information on any variability within the data.

In my freshman science course, we've been working on designing experiments to collect reliable and relevant data that can answer a question. Although we've focused on sampling issues, tools, context and the mindset of being a skeptic, I feel like the list of habits of mind provided by Lee & Tran provide a much more comprehensive approach to data collection that includes specific skills/practices that we can hone. In my junior-level chemistry classes, students are creating their own infographic posters to represent significant data about nuclear energy and disasters, and in reading the "data, data, everywhere" text, I realized that this would be a great opportunity to start discussing, with more guidance than I've yet provided, the reasoning behind and impact of using different types of representations for data analysis. In general, I really appreciate the emphasis of NGSS and CC or skills and practices of scientists (and simply, problem solvers) as opposed to just content knowledge and I am hoping that our vital signs training will help me to target specific skills and practices to help my students critically evaluating data. I'm also excited about attending training with a peer (and AP Stats teacher!) from our school as I hope we'll be able to collaborate on a project for some of our classes--and, that she'll help me to develop a better grasp on statistical data analysis!

After reading but having little prior experience with vital signs, I feel strongly that I can contribute to a climate of integration where each discipline has value in all of the classes regardless of the activity. I can support the work in the science class by helping students find suitable methods to graph data in meaningful ways. Then we can interpret our graphs and data and start finding trends. I am hoping to take home strategies for blending our science and math classes.

Students should understand the differences between qualitative and quantitative data and how to collect and analyze each one of them. They should understand variability in data and how to represent that graphically/statistically. When collecting data they should understand the importance of unbiased data and overall peer review of methods/data analysis/etc so that the reliability of their study is increased. All of these help students grasp how they can learn more about the world around them and what kind of sources to to trust.

Students in our programs currently work on collecting qualitative and quantitative data and experimental design to avoid bias.

I would like them to progress to understanding peer review and how to analyze and really understand their data (what does variability mean? When can we say that two things are 'different' with enough certainty?)

The other teachers I work with are largely interns and summer science education staff. Because I help train these individuals it would be relatively easy to work with them towards developing a curriculum that focuses more on in depth data analysis and processing. We have a new course that will be research project based next summer that should give us the actual time with the students that this can be a reality.

I currently teach 6th and 7th grade but have also taught 8th. I think this would look different at every level. Students in 6th grade classes might work on collecting, analyzing and displaying data on a basic level. As students progress through the grades, they should develop a deeper understanding of the importance of accurate data collection and interpretation. Students in eighth grade might develop a more critical view of data, deciding what is important, what is not, what are the outliers, why are there outliers, etc. Regardless, I believe that the best way for students to become critical thinkers around data is continual exposure to meaningful data.

In my class, I think I do a good job of having students collect, analyze and display data, but I would like to help them develop a deeper understanding of why this is important.

I am here with the both 7th grade math and science teachers so I am hopeful we will be able to develop some ideas together.

What are important skills and understandings for students to develop around data? That some data changes as we gather it and some data can be separated into types, data can be represented visually after analyzing it, and students should question/examine closely the findings and methodology of conclusions that are drawn from any data (simply relying on central tendencies of measure is not enough, looking at outliers is half the fun!) Why are they important? To develop critical thinkers who can look beyond the first impressions of the data and do some self directed digging into results and questioning.

Which of these are students working on in your class? Which of these would you like them to work on? As the school 6/7 GT consultant, I do not have a science class. I offer extensions/enrichments like Junior Solar Sprint (good for all students but no one does it Grade 6/7), LEGO robotics (good for all, but not offered 4-8) & Google CS coding clubs. I would like to offer something with life sciences. (We used to participate in W.E.T at Wells Reserve, but now most of the water quality monitoring students helped with is automated.) I facilitate advanced math class (stream live from high school for one or two kids),help to screen the larger middle school accelerated cohort, coach Math Olympiads for ID'd kids as enrichment, but am not teacher of record for math or science students. I am their LA teacher of record, though, and I use Junior Great Books ''What on Earth'' & ''Keeping Things Whole'' anthologies – examining human interactions with our planet. I know a connection is just waiting to be made with Vital Signs and my LA class, examining the school grounds and our little pond out back.

Which of these would you like them to work on? Maybe once we establish what problems exist on our campus (bittersweet...others?) and see what the pond holds in store, students can plan an experiment around what we find and try to affect the outcome.
How can you imagine working with other teachers in your team or school? Since this is good for all kids, maybe I pilot this, share with interested science and math teachers and offer to partner with a team to make this experience available to more students. Two science teachers were interested in attending this workshop with me, but timing was the issue. I have a fixed schedule, but there is one block I can be in regular classroom and/or ''consult'' if it is someone's planning block.

What are important skills and understandings for students to develop around data? Why are they important?

From the STIERS article, I will be able to make a great introductory lesson to sampling and bias (even for AP Statistics Students). Excellent points that were made were the concept of sampling as a representation, random vs. what we think is random, and how our thoughts and preferences create bias.

· Which of these are students working on in your class?

We have not started sampling or bias so this will be a good resource. In addition, I will read the other selections to see what else I could use to supplement the curriculum and create meaningful learning experiences.

· Which of these would you like them to work on?

Again, both sampling and bias are a part of our curriculum. We will work on them both.

· How can you imagine working with other teachers in your team or school?

Susan and I are discussing this. We touch base about every other day. We share ideas that we could work together and/or our department members could work together.

We are attending the workshop together and we hope this is the beginning of interdisciplinary learning between our content areas.

The Stier reading discussed the importance of students understanding sampling methods when collecting data. I had never thought about connecting an experience collecting data to the importance of sampling, likely because I find it a very simple concept for myself to understand with a wildlife background. I am sure discussions with students would reveal this isn’t true for them at all, and by doing an activity such as the tree sampling one in the reading, they would leave with a better appreciation of what questions to think of and ask when examining other people’s data. To realize that bias is a huge part of data and will affect our perceptions.
This year students will be working on being precise with how we collect data, and then using data as evidence to support or reject a claim.
As a math teacher I would love to do data analysis in math class for data collected in science. It would be great to create an interdisciplinary experience, using data as the math focus.

What are important skills and understandings for students to develop around data? Why are they important?
Students need to know how to ask questions that they can collect data on to explore visually and match with other research/information, to help them formulate conclusions. They also need to begin to understand that science is always being tested through new experiments, questions, research, data collection...

Which of these are students working on in your class?
I do not teach science class. However, I am thinking about some ethics data collection projects students could do:)I will be working with science teachers around the building on this too.

Hi fishoutside!

I like the sounds of this ethics data collection project. I am excited to learn more about it and for you to have time on Friday to collaborate with other teachers from your school and around the state.

Data collection should be context based and the results open to interpretation. The methods of collection, as well as conclusions drawn, are inherently uncertain and available for skeptical examination.

I would like my students in my science classes to develop a deeper understanding between collecting data and interpreting it. Often data is collected as a measurement, graphed, and the examination of the results is shallow. This process is mathematical and the connection to context is weak, at best. Outliers are simply dismissed as irregular, and variations in results are often seen as evidence of having done something "wrong" in data collection. The connection between the claim and data is either "supports" or "doesn't support" with very little explanation of why. I also want students to see the connection between the question and the method of data collection - to generate their own methods of data collection based on the context and to be able to defend their method as the best way to examine the question.

A number of teachers from my school are attending and I think collaboration will provide for more ideas and support for me, as well as more opportunities for my students to examine data and conclusions from similar work from other classes. Often students are hesitant to scrutinize their own results but readily do so with other students' results. Informed skepticism is something I would love to see developed across the school.

Hi 317vitalsigns,

We will be focusing a lot on variability in data and I think you will get a lot of good ideas about how to develop student's skills in data literacy, especially the ability to scrutinize their results. I am glad you are coming with other teachers from your school too, this will be a great day to collaborate and build off of new ideas.

Students should develop an understanding of what it means for data to be randomized and biased, beyond understanding these terms students should understand how these two aspects can correlate and what role that plays on the data analysis. Sampling is another important concept for students to comprehend.
In science class students are learning about complex systems; sampling has to do with this because in complex system students must learn about representative parts of the entire system and then acknowledge how those parts work together as one. In math students will be working with data.
From a science point of view, I would want my students to obtain a deeper understanding of sampling- directly or indirectly related to complex systems.
It would be great to be able to interrelate the science and math lessons/curriculum of sampling, randomization, and bias together- Having these two classes working with the same data/material when covering this topic will provide a better foundation for the students to learn from.

Hi Janemarston!

We will be going through our new biodiversity data investigation curriculum on Friday and there are some great resources around random sampling and the importance of sampling in data analysis. I think you'll find that Vital Signs can be a great way to engage students in the idea of complex systems while also allowing them to think about sampling methodology and the concepts of randomization and bias.

Looking forward to working with you on Friday!

Students in my 6th grade Math class typically work on a Data unit, but mostly at an A level of statistical sophistication. Important skills for my students to develop are collecting data, representing it on a graph, and analyzing data. I would like them to work on having a deeper understanding of looking for bias on graphs and how they can be used to mislead people. I would also like them to develop an understanding of the importance of data in our daily life by making meaningful connections (choosing what data to collect, relating it to another subject in school by collaborating with the Science teacher on my team (Erin Overlock), etc.)

Hi jdumont!

We are excited to work together on Friday, and I think that the curriculum and ideas that we explore will help your students think more critically about data and how it's represented.

Looking forward to sharing more ideas soon.