The Next Wave

In February and early March, I had the opportunity to teach my first college-level course. My audience was student teachers and the topic was effective data use.

I was both excited and a little terrified. It was a great opportunity to share some learning on an important topic that doesn't often get much attention as teachers prepare to join the workforce. But, it was designated as a 10-hour elective, so I made myself think of it as an extended workshop. A few years ago, I did a Data Academy in my district that consisted of six 90-minute sessions...so it didn't feel like too big of a stretch to do five 2-hour sessions. Since the Data Academy, I have also developed and presented a lot of other content at various conferences and in other spaces. The twist on all of this was that I needed to target an entirely new audience.

Syllabus
I used a framework from this article to organize the course: Mandinach, E. B., & Gummer, E. S. (2016). What does it mean for teachers to be data literate: Laying out the skills, knowledge, and dispositions. Teaching and Teacher Education, 60, 366-376. During the first session, I had the students identify their level of familiarity with each of the five major areas of the framework, along with the items under each that they'd most like to learn. This provided me with some direction for the rest of the sessions.

You can access my course materials here: https://github.com/tlricherson/TESC_MIT_Data.

How it all went down
I didn't do much in the way of assignments. I asked them to read two research articles and we used two examples from Observe, Collect, Draw to provide them with some practice collecting and representing data. I really just wanted them to immerse themselves in the discussions during our time together. It was, after all, an elective...and they were plenty stressed out with other coursework. I wanted them to have a positive experience with data.

We also did some activities modified from the Data Therapy project. These included the paper spreadsheet, find a story, and build a sculpture. I had been wanting to try some of these for awhile and hadn't had a group for this. My favourite was the sculpture activity. I've had the coloured blocks and tiles for a couple of years and it was great to provide them, along with some data, and have small groups of students physically model a story they thought was important to tell from the data. I didn't allow them to write or annotate until the very end. (We did three rounds of data/revision.) I really enjoyed hearing their thoughts about that experience. Many of them noticed the same things that I have about manipulating data physically with your hands. It's such a powerful and personal experience. Magical.

Lessons learned
I think I did an okay job. Most of the time, I paced things well and brought the right resources. As always, I should have aimed for "Less me, more them." I would have liked to structure the discussions a bit better and given them more time to practice using data when we were together. We didn't have access to a computer lab and not everyone had a laptop, so I didn't spend any time on Excel basics, which I think would have been one of the most useful things to send them out the door with. But, I did give them some rich opportunities to think with data...and that will serve them well.

I heard from a professor in the program that students talked about my class a lot in their other classes...that they were showing her lots of great pictures of their work...and that a few had said it was the highlight of the winter quarter for them. The students themselves gave me a wonderful thank you card, a $50 gift card, and a little notebook to use for capturing data. Very sweet of them!

I don't know if I'll get the opportunity to teach the class again. This particular format was brand new for the university and they will need to evaluate its success before making decisions about next year. I am so grateful for the opportunity...and also that I was able to finish the class just moments before the transition to all classes being online. I greatly enjoyed being with these almost-beginning teachers. The next wave coming to our classrooms is going to be amazing.

I was taking a break from presenting this year. And then I got asked to share some of my data stories at a conference session in December...and asked to develop this university course...and a couple of other things, too. I said "Yes" to all of them, even if they were daunting. I am glad that as the world becomes more closed for the next year or so that I had the opportunity to reach out in those ways. I have to believe that there will be chances to do so again. I hope all of you are finding ways to share and connect and celebrate learning from wherever you are holding in place.

Coming Soon: The Data Lab

I know it's been quiet here...but I'm still around, thinking and working on various things. My latest data story will be complete this week. It's taken a few months to represent nearly 10,000 data points, but it is looking good. More on that soon.

But today, I want to commit publicly to what's next.

It's been a challenging year at work. I still enjoy my job a lot, but not necessarily the conditions I have to currently work under. Enough said. So, as I've been talking with others about this and pondering what I want to do, I have found myself thinking about what I want. What would my job look like? And in the midst of all that, I developed what I started calling "Crazy Idea #1" and "Crazy Idea #2."

Crazy Idea #1: Community-based Data Story
I've pushed out our district data stories into the community for the last couple of years, but what if I helped the community push out one of its own? What if I worked with an organization that needed community input on their strategic plan or other goals? What if we linked with other districts to leverage our data and resources?

And, crazy or not, this idea is in motion. I've identified an organization that is working to help students in our area build their capacity to connect with their neighbourhoods and community. I've talked with my counterparts in other districts about some data that we have in common to share. And soon, I'll be working with a few thousand students to create a data story that we will share at our city's spring arts walk. It's terrifying and inspiring...the perfect intersection of emotions to get me excited about going to work (regardless of whoever and whatever else is there).

But most importantly, I plan to use Crazy Idea #1 to launch something even crazier.

Crazy Idea #2: The Data Lab
You see, what I really want to do is support people in using data to answer their own questions and tell their own stories. And while not all of those stories need to take a physical shape, I can honestly say that getting your hands involved builds understanding. So, to that end, I want to develop a physical space for people to come and work with data.

I see this as a storefront in our downtown area. The front would have some retail options—journals, art supplies, all manner of sticky notes, and anything else you might need for capturing and representing ideas with data. But the biggest part of the store would be a conference space...something with flexible furniture, idea paint on the walls, carts with materials, a large screen, and anything else needed for learning. I see this as a place to host workshops on all sorts of topics, data walks, group work/planning, and more. It will be a lab for building stories. I want it to have a 3D printer and laser engraver and band saw.

And my audience? Being in the state capital, there are plenty of options—from lobbyists to state agencies to schools to community-based organizations. Most importantly, I want it to be a place where all are welcome and that underrepresented groups can have their voices lifted. I want to support and grow others.

But to get there, I have to build my reputation outside of school districts and demand among other organizations. I need some time to build capital (social and monetary) through consulting so I can have enough momentum to launch the physical space. Crazy Idea #1 is going to be one of those steps.

In the meantime, I have commissioned the logo you see above. (It's not finalized yet...we're still making a few edits.) I am teaching a class on data use at a local university this spring, and that will give me an opportunity to test out some hands-on workshop ideas. I've purchased a couple of domains. And I'm off to meet with the local center for women in business to try and get smart about that side of things.

When I talk about this idea with people who know me and know my work, they all see the potential. And while I know that they're biased (as am I), I've also never been so clear on what I want in my life...not even when I picked teaching for a career. I realize that there will be lots of twists and turns on the path ahead...plenty of setbacks and disappointments...and that the final product will be different from the vision I have now. But I accept that as part of the bargain.

What do you think? Any feedback on the logo or ideas? Are there people I should talk to who do similar work? What else would you advise?

Road Map

I consider myself an organized person, but not much of a planner. At least, I don't do a lot of long term planning. I have never had a career path that I've mapped out. I didn't decide I wanted to be a teacher until the month I graduated from college...and since then, I've more or less fallen into different jobs when recognized Opportunity knocking at the door. I am also a fan of her sister,  Serendipity. In fact, this is one of the reasons why my current home is my favourite place I've ever lived. There are little bits of magic and wonder to be found every day. I don't offer or condone any of this as the best approach to life. I am always in awe of those who have clear goals and seem to be driven toward them. It just hasn't been my experience...and I am okay with this.

So, imagine my surprise when, by chance, I found myself writing a theory of action, developing a logic model, and outlining a plan for some long-term goals with a data initiative. Who the hell am I becoming in my old age? But if you've been following my journey here over the last year or so, maybe some of what I share below will not be a surprise. In fact, I'm hoping that some of you might like to play along, too.

Theory of action
Here is my current, messy thinking: 

If we increase data literacy in ourselves and others, then participation in conversations at school and with the community will become more equitable, and then structural and institutional barriers to education will be reduced.

I've spent a lot of time in the last couple of years trying to ground myself in what I believe about data and the purpose it serves in education. I might summarize this as that I don't think that we can solve problems by representing our data in the same ways and having the same conversations as we have before. Whether your call it an achievement gap, opportunity gap, or educational debt, the bottom line is that we've been well aware of disproportionate outcomes for a long time...and yet another bar chart showing this isn't going to be the thing that creates change. I won't claim that I have THE answer or any sort of magic bullet, but I do have something different. I think that's the best place to start.

The plan
I've been working on some ideas related to community engagement with data, building data literacy in parent groups, and empowering underrepresented voices to tell their stories. And the more I read and think and develop these ideas, the more I recognize that there are some goals and outcomes that are bigger than I'd ever imagined. Serendipity has been an incredible guide and inspiration to this point, but I can't make the next leap (or two) with her alone. I'm going to have to have some real help.

Stage one: Build capacity in self
Not to be intentionally selfish, but this part of the process really is all about me. Perhaps you have projects where you are in the same mode. This has been a long-gestating stage. I went to my first Tapestry and Eyeo conferences more than two years ago. I've been building and sharing data stories in our district office for nearly that long. On the way, I've had to pick up new tools and skills and increase my personal network to call on experts and mentors. I don't believe that this stage will ever end—I will always be a learner. But I also think it's important to call it out separately as a base for everything else I want to support.

Stage two: Build capacity in organization
This past year, I've worked on not just sharing what I've learned at presentations and blog posts, but also leading workshops and building GitHub sites with resources. I've now seen others build their own data stories to share and grounded school leaders in our district in basic data literacy.

Stage three: Build partnerships outside of the organization
I am working on finding spaces outside of our district to host our data stories. Currently, Ready or Not is at our regional educational office and our story on graduation is at the state department of education. And last week, in a frisson of why-the-hell-not, I cold-called the data analytics business downtown and asked if they would host a window display during our city's fall Arts Walk. You see, I've recently been building "short stories"—smaller versions of the big displays—to take on the road. And while I won't claim that they are art, they are beautiful and good conversation starters. Why shouldn't I share them at a community event?

Another piece of stage three is a pilot project for next year where we will use some of the data therapy activities and other resources to increase data literacy in a parent or community group. But most importantly, this is not a project solely about pushing out some learning that we think is critical. It is about an opportunity to listen to the questions others have about our schools, as well as help them tell their own stories about what matters most to them about education. I am super-excited about this, even if I have no clue right now how to make this all happen.

Stage four: Empower the community
On one hand, this is really just an extension of stage three. If we do a pilot this year, then we will scale up afterward. But this is also where things get so big that it can't be "my" project anymore. This is a good thing. It means that I've been able to build enough capacity and partnerships that I can take a supporting role. What will all this look like? It might be a lot like the work showcased over at Making Sense. They have a whole toolkit ready and waiting. I also 💕 love 💕 this article on Data in Place: Thinking through Relations between Data and Community. I don't know what the outputs of this project will look like for us because we haven't implemented all of stage three yet. We will have to wait and see what our stakeholders think is the most critical issue to address.

So, there you have it. My plans for world data domination. Okay, maybe not as grand as all that, but I am hoping for a ripple that one day can become a wave. And this is where you come in, too, because everyone is welcome to join in. Are there activities you want to try, too, so we can learn from each other? Do you have connections or resources to share? What feedback or ideas do you have for us?

Walls that invite others in: Transform your conversations about data

Last spring, I was invited to put together a 3.5 hour workshop for our state assessment conference that happens every December. I was told that the topic could be anything I wished. And, of course I agreed to do just that and hastily wrote a description in early June...and by the time my summer holiday started in July, I was already panicking. What the hell had I written? How was I going to deliver on this description?

Public narratives about schools often focus on measures of student performance. However, students are more than the sum of their test scores, demographics, and program participation. Join our conversation about how to repurpose and leverage data walls to create, inspire, and communicate with audiences about what matters most. As part of this interactive session, we will share examples of innovative data stories from both school and district levels, as well as tools and strategies for constructing new narratives about student and school outcomes.

Basically, I said I would facilitate some learning around how to build the sort of data (story) walls we've been doing recently. This sounds great on the surface. I truly believe that we have change the types of conversations we are having with and about data in education. In practicality, however, it turns out to be really challenging to develop guidance on how to listen critically for opportunities to transform these interactions...much less how to tap into and be confident about being creative with displays. As Isaac Asimov said, "The world in general disapproves of creativity...and to be creative in public is particularly bad."

I made a lot of notes this summer based around my own questions about using data, and this fall, I've been chipping away at organizing all my notes from the last 18 months into some sort of outline. Combined with the data academy work I'm guiding this fall, I have felt overwhelmed by the amount of adult learning I need to generate...all while trying to do my "regular" work.

https://twitter.com/science_goddess/status/930421496538841088

But, at long last, I think I'm ready for this workshop...which is a good thing, because it will happen on Wednesday. I don't have a lot of time left to fuss with it. It's time to fish or get off the pot, so to speak.

The slide deck is 150 slides (and 90 MB). I have around 10,000 words in my speaker notes. I've incorporated references to King Kong, Frankenstein, Pink Floyd, ETA Hoffman, and The Inferno. And, I've built a companion site on GitHub for all of the other links, references, handouts, and structure.

We'll see how this goes. Three and a half hours is a long time to spend with 40'ish people on one topic. The whole premise---building these oversized, experiential data installations---requires a different sort of investment and risk-taking on their part. I am not foolish enough to believe that they will all go back to their schools and districts and put up these displays. But let's say three of them do. What a wonderful start...and how I would love to know of others who are doing this work. It all has to start somewhere. I will plant seeds now and see what sprouts.

Make the connection: Student growth to teacher action

I have had the privilege of presenting at the ASCD annual conference over several years. I've been an ASCD member nearly my whole career. It's an organization that, as the rebranded conference name suggests, empowers educators in all roles to support students.

This year, I am presenting on the qualitative side of data. My session description is "If 'not everything that counts can be counted,' as Albert Einstein suggested, then how do we measure and represent student growth beyond test scores and grades? In this interactive session, you will learn strategies that capture student learning in multiple ways, as well as how to communicate feedback about the whole child using data visualization. Join the conversation about how to apply digital and analog tools to tell your students' stories and report the full spectrum of student learning."

The challenge of doing a presentation like this is that I have to submit the description more than six months before the conference. Whatever it is that I had in mind to talk about in August was long gone before I received notification that the proposal was accepted...let alone when I sat down to build the content. I am influenced, too, by all the things I have learned in the interim.

The basic story arc did finally emerge. I'll start first by talking a bit about why data visualization can be a powerful tool. This is my usual lead-in, and I think it helps to provide a few easy to grasp examples before launching into new territory. The next hook is to talk about achievement data. Now, this particular piece does not explicitly fit the session description, but my goal is to move from the larger scope of the purpose of data viz to what we typically see in education, and finally into non-traditional ways to represent education data...and perhaps even a little further than that.

I heard a presenter this morning say that "schools embrace business ideas as they are fading." In other words, what was hot in the private sector 5 or 10 years ago becomes the things that schools are talking about now. I have seen this happen a lot over the course of my career. And what worries me most now is that decisions about data privacy and access are being made now that will affect schools in ways they haven't even anticipated yet. I am not going to claim that I can change the world with my presentation and suddenly schools will make these conversations a priority...but it's a start.

My call to action for them is around being in control of creating their own narratives using data and to think about what they want to represent, not necessarily what they are told to represent. All too often, the public view of school data is just annual test scores. But children are so much more than the sum of their test scores. They deserve a more robust approach to sharing their stories (and to be involved in that process, as well).

I have an ancient (by web standards) wiki where I have placed materials for this session. Someday, I'll move everything over to GitHub...but for now, it's a reminder of the journey I've taken to this point and perhaps a place to shape the ideas ahead.

Eyeo 2016 Recap

I attended the Eyeo Festival this week. It brings together "creative coders, data designers, artists, and attendees." I have been wanting to go for a couple of years as a way to pull myself in a different direction. It's easy to get into a rut, or at least into a routine that doesn't allow you to ponder other possibilities. This was a very different conference from others that I've attended. Here, I came away feeling creative and inspired. At others, I've walked away with learning to apply. It's not that one outcome is better than another---they each have a role.

I am looking forward to the videos from the festival being posted. In the meantime, here are some of the highlights.

Emergence
Nicky Case kicked things off. His focus was on emergence, a concept where the sum is different from the parts. I can't say that he shared anything new in terms of his ideas, but what I liked was seeing a young adult share his process of learning that there is a lot of grey area in the world. I worked with teenagers for nearly 20 years, and the black/white worldview was pretty normal. It takes time and experience to learn that there are lots of answers to any question. As a young 20-something, Case is showcasing the transition to a more experienced lens on the world.

The keynote by Paola Antonelli, which was the next evening, shared an even more advanced take on this theme with her views on quantum design: "ambiguous states, in the spaces ‘in between’—between digital and physical, high-tech and crafts, old and new, nature and artifice, developed and emerging world." Beauty is not just in the eye of the beholder, meaning is derived from the eye of the observer.

Transformation
A second theme was about the transformative nature of data. Paolo Ciuccarelli of Density Design spoke about the poetics of data visualization. He pointed to the need to design data experiences that "generate poesis within a space of wonder."

from http://www.densitydesign.org/research/brain-houses-three-interieurs-stories/

One of my favourite ideas that he shared was this concept of a panorama, like the one shown above. I love the idea of embedding the data within a larger context. I highly recommend having a look at the Raw tool for generating visualizations.

Moritz Stefaner gave a talk on his Data Cuisine project. One of the things I liked most about this project was the idea that the dimensions of food (ingredients, presentation, cooking method, etc.) can be used to represent dimensions of data. This leads to a very different sort of interactive experience.

Transformation also appeared in how artists used materials in different ways. Whether it was Anouk Wipprecht combining her love of couture and robots or Tania Candiani speaking about the intersection of combination, serendipity and translation, I was blown away by the creative thought processes that were shared.



This is not the sort of end product I get at education conferences---where sharing one's thinking is not considered good enough. At those conferences, there is an expectation of audience involvement and tangible takeaways. With Eyeo, the feeling that is created through the presentation is the goal. I can't talk about this conference in terms what I learned, but rather, how it made me feel. This brings me to the last major theme.

Instruments of Power
There was a strong focus on equity at this conference, from the range of speakers, to topics, to the code of conduct. Part of that is an understanding of privilege as it applies to how we collect, use, and represent data.

Marek Tuszynski from the Tactical Technology Collective shared their recent exhibition: The View from the White Room. (E.g. looking out from an Apple store.) The show looked at questions such as What does it mean to live in a quantified society? and What is the value of data privacy when it becomes something you can buy? Lots of powerful things to think about from this session---I had to get out and take a walk after it. Part of the exhibit included something called Big Mama, based on the quote from a government official justifying surveillance that he did it because "I love you all." and the perception that the contribution of data leads to a harmonious society. Take a deeper look at Unfit-bits, Me and My Shadow, Security in a Box, and Exposing the Invisible. It is not that these concepts are new or unknown, but it's their application within our personal and professional contexts that make them worth revisiting.

As much as we talk about the power data visualization has to reveal, we rarely talk about how it can also be used to hide. In the best talk I saw, Josh Begley shaped conversation around what the work is that data visualization does. In one example, he talked about the geography of incarceration. As part of that, he made the comment that "most photos today are taken by machines for other machines to see." Satellites, drones, and other tools capture far more images than anything humans post to Instagram, Flickr, or other sites. Josh works on projects that bridge what machines are doing with what we notice. Do we want to be as connected to our foreign policy as we are to our phones? Check out his work on the Dronestream App or Officer Involved Shootings as ways to explore how the things we don't represent are still powerful enough to evoke emotion.

There were other presentations, keynotes, and sessions that I attended. There were also some I didn't get to attend due to having to get to the airport...including one I was looking forward to the most by Lynn Cherny. However, I enjoyed exploring a bit of Minneapolis, getting to meet several data viz heroes in person, and being able to think about some very different concepts for awhile. This spring has been a real drag in terms of work demands. I am looking forward to working on some new projects that are being spurred by this recent boost to my sense of creativity.

What have you seen recently that inspires you?

Stories, Not Atoms

This is the 100th post for this blog, and while it has not always featured Excel, it has always tried to keep a focus on telling the best stories we can with data. I've been thinking about the future...how storytelling with data may evolve. The recent Tapestry Conference was just what I needed to spur me creatively and think about the next stories to tell.

I have a few conference posts to share in the coming weeks, but will wait to publish them until the videos are available. I hope that you will appreciate the presentations as much as I did for the diverse lenses represented and how presenters tell stories with their data. We all have our challenges with data quality, helping our peers and audience become more data literate, and the storytelling process. For now, I'd like to share my takeaways and next steps.

Continue Sketching
I draw very poorly. I haven't had an art class since elementary school, and I assure you that was many many years ago. But I find that when working with data, drawing things by hand is a critical part of the storytelling process. I keep a notebook and coloured pens with me nearly all the time. The notebook is a place to just dump ideas. I find myself jotting down various things while I'm in meetings, out for a bite to eat, or even on the plane home from the conference. Not all ideas make it into production, but having them captured in one place is extremely useful.

Thinking about how to display attendance

Catherine Madden and Nick Sousanis both spoke to the importance of recording and communicating with visuals. More on this in other posts, but if you're not using sketches to draft or sort through your data, I encourage you to try it. No one has to see these. They'll just be pleasantly amazed at the final product.

Be Open with Your Audience
This seems obvious, but the presenters at Tapestry put some new spin on the idea. Alan Smith spoke about supporting our peers in becoming competent critics, Enrico Bertini implored academics and practitioners to connect and collaborate, and Eva Galanes-Rosenbaum encouraged us to be transparent about the sources and quality of our data.

Photo by Ben Jones from Bertini's presentation; This slide has good advice for educators, too.

This sense of openness really does need to be mutual. It's one thing to tell an audience that your story is missing some data or is of dubious provenance...and it's another for the audience that you tell the story in specific ways. Scott Klein presented a nice timeline of how data visualization has developed as a journalistic endeavor. This includes educating readers on how to interpret a line chart. Jessica Hullman talked about the types of sequencing with visuals that readers prefer. These lessons are useful, but they are not the whole picture. As an audience, we have a responsibility to be open to new types of visuals and stories. We have to be willing to engage and grow.

Seek New Territory to Explore
I met a lot of people this week. Some I've only known from an online presence, others I would never have connected with had Tapestry not brought us together. It was good for me to get out of my little box that is normal life, but this also applies to the wide variety of boxes in which we work. Sousanis showed us how comics and graphic novels encourage narratives to bleed over the edges to create new directions. This message was a little at odds with Jessica Hullman's presentation on her research on how to generate the right sequence for stories, as well as Trina Chiasson's look into creating data selfies. We like things that are predictable...but we are creatures that like novelty, too.

The opening slide at Tapestry quoted Muriel Rukeyser: The universe is made of stories, not atoms. As I continue to think about this push-pull between staying safe in the universe we create and the need to explore beyond those borders, I've come up with an idea to try for next year. Maybe you'd like to play along, too.

I'd like to tell ten new stories about my school district next year---one for each month we have classes. It's convenient that we have ten schools, but I don't know that they have to based that way. Maybe there should be a month about attendance or early learning. The views of different stakeholders could be featured. Or perhaps something more Dear Data-like, capturing a month of meetings in the board room. I want to use a bulletin board in our district office for some offline data viz...as well as links to some online data to explore.

That's my ambition, anyway. I'm using my sketchbook to gather all kinds of ideas now and maybe this summer I can start putting the structure in place. By putting this goal out here...making it public...I hope you'll keep me honest and on target with it. And of course, you're more than welcome to do something similar in your own school.

So here's to the next 100 posts for this blog. There are lots of stories left to be told.

Go Tell It on the Mountain

I am stretching this week beyond the comfort and confines of my typical environment in P-12 public education. I'm at a convening of data storytellers from a large variety of industries. It's the first time I've been to a conference that is not specific to education.

About 100 of us are safely tucked away at the Stanley Hotel (you know, the one the inspired The Shining?) in Estes Park, Colorado, for the Tapestry Conference. As far as I know, I'm the only public ed person skulking around---although there are several higher education representatives. It is odd, for me, to meet and greet with people from Zillow, Comcast, ProPublica, or NBC News. Every face is new to me, although I finally met Robert Kosara and Naomi Robbins...both of whom I've been wanting to meet for a long time.  I love that everyone is passionate about the same goal of effective storytelling with data.

I have that interest and commitment to quality communications using data. But why else am I here? After all, I am definitely in the "one of these things is not like the others" category. I am here because public education needs to connect with everyone. It's public, for crying out loud. Everyone's tax dollars are funding it. Regardless of the industry you represent, there is a connection with public education. I hear all the time from educators who are tired of how others message our work. We can change that, but not by sticking to our own circles of influence and expecting the rest of the mountain to come to us. Sometimes, we have to go to the mountain.

Beyond this idea, however, is a more personal one for me: I need to learn and grow in my professional work. I get an opportunity to do that through education conferences---they help me learn about my job. But there is something beyond that...something that speaks to the purpose of what I do and feeds my spirit for it. That is what I am hoping Tapestry will be for me. This is not about the nuts and bolts of my day-to-day job. This is about helping me inspire and grow others when I return to the office.

Learning is my life's work. It is easy to lose focus on that with a sea of emails, ever-present to do lists, and a calendar full of meetings. It is critical for me to set all of that aside for a couple of days and just immerse myself in learning. Networking with others is great, too, and a change of scenery doesn't hurt. But most of all, this is an opportunity to just be in that moment of growing my knowledge base.

We are not so different, educators. We may have small-batch, artisanal data sets and handcraft our visualizations in Excel, but we face the same challenges as Big Data when it comes to data quality, effective communication, messaging, and design. We have the same issues around helping people ask good questions of their data and identifying the most critical aspects for action and attention. Perhaps we have a better chance of finding solutions together, rather than isolating ourselves as educators. Together, we can move mountains.

Making Sense

Earlier this week, I had an opportunity to share three sets of data with building administrators. You've had a preview of some of the visuals: a new way to represent the achievement gap, cluster charts, and small multiples. The administrators had not, although I have shared lots of data in lots of other ways with them. This was our opportunity for some in-depth work.

With each round of data presented, I did a little bit of instruction so that they understood how to read the charts. Each table had some paper copies and a few focusing questions to get the conversation rolling. And then the real fun began.

I have never had a chance to watch people learn with new-to-them data representations. Bar charts, line charts, and scatter plots are commonplace. When you share these types of visuals, everyone already knows the drill. But hand people sheets with small multiples and a few of them will overlay the pages and hold them up to the light. Give them a set of line plots showing gaps among student groups, and they will spread them across the table to organize the pieces in different patterns. Hand over some cluster charts and watch and people fold the paper along various lines to build new learning.

It was absolutely fascinating.

As a way to gauge their engagement with the new charts, I tried the Talking Mats which were recently shared by Andy Kirk.

I provided three different colors of sticky dots, one with each round of data, and asked the administrators to place their dot when we transitioned to the next part of the workshop. In addition to watching them interact with the data---which was very powerful learning for me---the Talking Mats provided valuable feedback at the end. These are visuals for me, created by the audience, which have told me a lot about which charts gave the biggest bang for the buck. I'll know where to focus my time and work in the future.

A few people struggled with looking at the forest of data represented by small multiples, instead of the trees. Some made connections across the data sets. Still others wanted to argue with data because they were unnerved by what they were seeing for the first time. By the end, though, there was a very rich conversation about the meaning we'd been able to make from all of the data.

For the first time since I started this job, I had many public compliments about the work I shared. My favourite has been "Thanks for presenting data in a way that helps me learn." Here's to more opportunities to use Excel to support us in making sense of things.

New Frontiers

I have probably shared this before, but this tweet from Hilary Mason is something I think a lot about:

https://twitter.com/hmason/status/488382950128754688

Within my own work, I continue to raise conversations about equity. How will students and teachers be empowered by the data we collect and review? How do we provide opportunity for marginalized voices to be heard? How do we elevate their needs and concerns?

I am starting to collect resources around both equity in data visualization. Here are a few that you might be interested in, too:

• The Harvard Graduate School of Design recently hosted a Black in Design Conference. There's a great Q & A available, where organizers Cara Michell and Courtney Sharpe provide background.
• I was also pointed toward two different articles about feminist data visualization. One explores what this type of data visualization would look like. The other takes a historical approach, reviewing work of women engaging in data viz in the nineteenth century. 
• Along this vein, I am starting to see more information shared about the intersection between digital humanities and data visualization. You might also be interested in following Shannon Mattern, Lauren Klein, and Paige Morgan for more ideas in this field.

In other news, I have been working on a little behind the scenes cleanup on this site. I've refreshed the information on the various pages, as well as the front page side bar. I also recently purged my Delicious site, deleting dead or irrelevant links and reorganizing the remaining ones. If you're searching for Excel info, research, tools, or anything else related to data viz (including equity), please head over to that site. There, you can sort links by a variety of tags.

I'm heading to the Tapestry Conference and Eyeo Festival this year. I am feeling the need to stretch and grow beyond the field of education. I do my best to connect with others in a digital space to learn about how they are using data, but I would like to do some in-person networking, as well. Will any other readers be at either of these events? 

WERA 2015: Data Viz Workshop

I've done several presentations over the years about data visualization within public education. I've talked about graphic representations as a form of feedback, types of tools, guidelines for improving communication using visuals, and more. All have been brief 60 - 75 minute affairs with some very simple sorts of activities and conversations along the way.

This week, however, I had an opportunity to guide my first workshop. I had three and a half hours available to support educators in really digging into telling the best stories we can with our data. Having this sort of space and time available enabled me to think about the content differently. I've posted links to previous presentation materials here, and this post is no exception. For those of you who might be interested in scoping out the slides, materials, or links, head on over to ye olde dataviz wiki to take a look through the stash.

What I wanted most for the audience this time through was an opportunity for self-reflection and metacognition. Educators have relentless jobs. There is often no chance to think about what did or didn't work with a group of students today because they will be here again in the morning...and the tyranny of the urgent is to plan for that. I felt like it was important for our afternoon to be a time where people could become more aware of their own design process---no matter how simple or sophisticated it might be---and, more importantly, be inspired. I tried to bring in many different examples of current projects from a variety of fields. The best way to get out of your bar or line chart rut is to see where others have made departures.

I don't consider myself an expert in any of this. I do consider myself curious about it. I do see a significant need in our field to elevate our visual communications, as well as prepare our students to do the same. I want to continue these conversations and add what I can. I will refine my workshop materials and perhaps have another opportunity to engage in this work at another time. I enjoyed it and hope that it's the start of something bigger and better for our field.

Session Recap: Data Displays as Powerful Feedback

I had the pleasure of presenting at the ASCD annual conference last month. Each year, I stretch myself a little further in making connections between ideas, as well as between technology and content.

My session description: Developing visual literacy is a key skill for student success with Common Core State Standards. Students also need clear feedback about their progress. Using data displays, such as charts and graphs, we can integrate these goals and increase student achievement. In this interactive session, you will learn strategies that increase visual literacy and foster communication. You will also learn to effectively use data collected in classrooms as feedback with students. Both digital and analog tools for organizing and integrating data into lessons will be provided.

Session descriptions are written at least 10 months before the actual presentation happens. This extended timeline can explain why many sessions are not as promised, which is very frustrating for attendees. You pick something from the catalog that looks like it is the most perfect thing ever, only to show up and discover that the presenter has something different in mind. I try to stick as closely as possible to my submitted description, but I admit that I end up taking a little birdwalk here and there. It's hard not to---you learn so much in between submitting a proposal and actually presenting it. For me, a lot of that growth in learning has occurred to changing jobs this year and getting a much better on the ground view of the lack of visual literacy among students and teachers.

My logic model that framed my presentation was

I started the presentation with a brief look at visual communication in general---pictures have been used far longer than text. Then, we talked about how graphics used as feedback have a larger impact on student achievement than nearly any other type of feedback (e.g., marking answers right/wrong). All of this was to build a case for becoming visually literate.

I won't bore you with all the details. I fused together some previous presentation materials and pulled a lot of pieces of this blog in as examples. But if you want a look at things, I have it all stashed on the same wiki as my other resources.

I was slated for 8 a.m. on the last day of the conference---not quite the worst possible time slot, but just about. So, I had a small, but awesome crowd. Lots of comments afterward made me feel good, from one gentleman who said it was the best hour of the entire conference (and asked if there would be a Part II) to another with a very heady offer I'm kicking around.

Proposals for next year are due in a month, so I am already kicking around things to share. I think that I will put in something about using questions to focus data use...and something similar to this year on visual literacy skills. We have to expand our conversation about visual literacy. We work so hard in schools to be literate in other ways. We practice rules for grammar, punctuation, and different forms of writing...all with the goal of improving communication. But for the most part, the visuals developed are junk. And that needs to change.

In the meantime, there is SO much I want to learn. I would love to try and go to the Eyeo Festival next year. Or somehow wrangle an invitation to the Tapestry Conference. I'm feeling a need to get beyond the borders of education and exchange ideas and resources. I continue to do lots of reading and thinking (no matter how quiet I am here) and am always pondering what to learn next. Isn't that what we want for our schools, too?

Data Sharing for Good

On Sunday, I'm presenting a session at the ASCD annual conference on using data in the classroom. Along the way, we'll take a tour of chart selection for a data set, some best practices for data viz, and tools for moving beyond "admiring the data." Materials for the session, along with other sundry data viz resources are here.

I've tried to pull from a variety of sources...a few favourite quotes sprinkled in, like this one:

We'll play a little game with the When Excel Gives You Lemons data. You can play, too, by clicking here to choose a bachelor from the three below. (Turn your speakers up for the full effect.)

We'll explore a few different kinds of stories...and the problem with pie charts.

A detour to Sesame Street will help us think about pre-attentive attributes.

So, if you're in Los Angeles this weekend, stop by and learn with us. If you have ideas and resources to share, leave them in the comments.

Learning All the Time

Over the next two months, I am participating in three different Massive Online Open Courses (a/k/a "MOOCs"). It's good to remind myself now and then that the edge of my rut isn't the horizon. It's time for me to make my brain hurt again.

I've taken online courses before, but never with so many classmates---and not in such a low-stakes way. Although I want to make the best effort I can, not paying for the courses (or having them show up on a transcript) gives me a bit of an "out," if I get overwhelmed.

Here is what I've signed up for:

Computing for Data Analysis

This course started on Wednesday and runs until January 30 (and has ~40K people enrolled). Taught by Roger Peng from Johns Hopkins, the description states that "this course is about learning the fundamental computing skills necessary for effective data analysis. You will learn to program in R and to use R for reading data, writing functions, making informative graphs, and applying modern statistical methods." Yikes. I haven't had an ounce of formal programming coursework since high school---you know, back when BASIC and the TRS-III were king. But I hear about R a lot and am curious about how to use it. It's time for me to get on board.

So far, so good. I've completed watching the lectures for week one and have taken a ton of notes. I'm almost finished with the first programming assignment/quiz---just one question left that has me stumped. I know how to solve it with Excel. In fact, the entire assignment would be much easier (for me) in Excel. But I am trying not to "cheat" by doing it in Excel first and then checking my answers in R. I need to know how to program...and the only way to do that is to get my hands dirty with R.

The most important thing I've learned so far is that syntax can be an unforgiving master to serve. Excel will give you some leeway between upper and lower case, for example. But R is exacting for every piece. 

But, hey, I've survived the first week in good stead...and that's 25% of the course. I feel more confident (even if it's a false sense) than I did when I signed up for this. Maybe I really can do this.

Introduction to Infographics and Data Visualization

Some of you may remember posts on other data-minded blogs this fall about this course led by Alberto Cairo. This will be the second offering, starting on Saturday, January 12 and wrapping up on February 23. This time, it's bigger (6K students) and has a few more tools available.

From the syllabus: "This course is an introduction to the basics of the visual representation of data. In this class you will learn how to design successful charts and maps, and how to arrange them to compose cohesive storytelling pieces. We will also discuss ethical issues when designing graphics, and how the principles of Graphic Design and of Interaction Design apply to the visualization of information. The course will have a theoretical component, as we will cover the main rules of the discipline, and also a practical one, as you will learn how to use Adobe Illustrator or Tableau to design basic infographics and mock ups for interactive visualizations."

I'm totally psyched about giving this one a try. I'm excited about learning the basics of Illustrator. I've played around a bit with Tableau before, but this will give me a reason to go back and dive deeper.

Data Analysis

Because the overlap in the first two courses is apparently not enough for me, this course also starts this month (January 22) and then runs for 8 weeks. So, there will only be one week where I will have to juggle all three...and some time when I just have this one to manage (assuming I don't sign up for anything else). This one is a complement to the R programming class I've already started, and is taught by Jeff Leek, who is also from Johns Hopkins.

This course is billed as "an applied statistics course focusing on data analysis. The course will begin with an overview of how to organize, perform, and write-up data analyses. Then we will cover some of the most popular and widely used statistical methods like linear regression, principal components analysis, cross-validation, and p-values. Instead of focusing on mathematical details, the lectures will be designed to help you apply these techniques to real data using the R statistical programming language, interpret the results, and diagnose potential problems in your analysis. You will also have the opportunity to critique and assist your fellow classmates with their data analyses."

I like stats, but it has been awhile since I have flexed those muscles. Not as long as it has been for programming, fortunately. One of the reasons I am interested in this class is the chance to work with bigger data sets, while applying my nascent R skills and reawakening my statistical knowledge. It's a good application of things. 

I'm hoping that I won't be a MOOC dropout. I also know that I've signed up for a heavy dose of learning at a time when I have a ton of travel for work and several projects due. But Opportunity knocked and I've chosen to invite her in to stay for a bit. If she starts making a pest of herself, I'm giving myself the option of evicting her. These courses will be offered again. I can catch her on another round.

Are you taking any (or all) of these courses, too? I have a couple of study buddies lined up for the first two courses, but the more the merrier! What else are you learning this year?

The Exhausted, The Design-minded, The Few

Last month, I had the privilege of spending three days at a workshop by Stephen Few. I had a five-hour commute each day to the workshop, which made for a very long week, but I'm grateful I made the effort.

It was quite a contrast with the Tufte experience. Instead of a room of 600, I found a room of 60. This led to a lot more interaction between participants and with the presenter, something I appreciated. One of the biggest differences between Tufte and Few is their purpose in talking about design. Tufte is much more academic and esoteric---design as more form than function, in some ways. But Few, like most of us, recognizes that while it's all well and good to talk about what design should be, at some point, we have to get practical about things. This is his purpose in writing and presenting.

Another contrast between the two gurus is how they view the audience. Tufte's reflects his Ivory Tower existence, with a basic premise that you present the data and the audience decides how they want to evaluate and use it. Interactivity is great, I think, but most of the people I work with are not data literate. And judging from the conversation I had with several others at the Few workshop, their co-workers and audience are no better with data. Few's view of the interaction between designer and audience is that the designer should listen to what the audience needs/wants---and give that to them in a way selected by the designer that is the best format for the data. I find this to be a much more practical approach.

Organization
Each morning started with a "pop quiz"---a series of questions about the upcoming ideas for the day. I thought this was a great way to get things going, not just from a management perspective (latecomers didn't interrupt the presentation), but as a teaching strategy. I wish he'd set aside time at the end of the day for everyone to review their answers. Not doing so misses a fabulous opportunity for people to reflect on what they'd learned throughout the day.

Most of the day was a traditional lecture format, with a one-time small group assignment included. I would have liked him to break up the lecture with a few pauses for people to have some partner talk about ideas. There was a lot of material to process along the way. I have no beef that all of the examples were business focused---the workshops were targeted for that walk of life, and I am but a humble educator. But not everyone works with profits and losses. The principles of good data design may apply across the board, but not everyone's roles are the same. If we really want to make changes in the way we use data to communicate, there needs to be opportunity to think about how to apply new learning.

Lessons Learned 
He didn't share anything that you couldn't learn from reading his books, which was my only real disappointment. Not to say that his ideas about data design aren't worth a second (or third) tour through the material, but I believe that presenters should use "live" opportunities to extend their thinking. If we're there, we've probably read the material---help us take the next step.

All that being said, this was a worthwhile opportunity to learn---my quibbles are more about the way things were said than what was said. I would recommend the workshop to anyone interested in the basics of data design. Here are a few of my takeaways:

• I liked that nearly all of his examples were built in Excel. As he pointed out, Excel is not a design tool; however, it is a data tool that nearly everyone has...and if you can make something look good with Excel, then you have no reason not to make your data shine elsewhere.
• For Few, what makes a dashboard unique (vs. other reporting tools), is it's purpose: monitoring. It should allow the audience to scan the big picture, zoom in on specifics, and link to supporting details. He really pushes the idea that there should be no scrolling---the dashboard should fit a single screen---but in a time where you can't guarantee which device will be used to view the data, I don't know that you can make no-scroll a "must." The best you can do is limit it by being thoughtful about what you present.
• Details matter. I think this is the one piece that is most misunderstood by most people. The colors you choose, the lines you use, the way your organize content should be just as agonized over as the data quality going in and the questions you draw out. Typically, this piece is tossed aside. If it wasn't, there would be so many crappy visualizations out there.

I'll share a bit more in the next two posts. Come back for a look at Few's most recent design contest (with a classroom focus) and my take on one of the visuals presented.

Bonus Round
Hadn't seen this clip from The Onion before...but it was the very first thing shared at the workshop. Thought you might enjoy it, too.

A Voice from the Wilderness and the Tufte Course

Even if I don't have much to show here over the last few months, it's been a busy time of things with data viz and Excel for me. Time to catch up, don't you think?

I want to start with July, when I had the opportunity to attend a workshop by Edward Tufte---the godfather of data visualization. Business types probably don't blink at a $380 fee for a one-day course, but for someone who works in education, I was a bit worried about the cost. I looked around online for reviews of his presentations. Surely someone had attended one and blogged about it, right? But my Google Fu was weak and I didn't find one. Robert Kosara (a/k/a Eager Eyes) attended the same day I did and has posted an excellent review. I agree with many of his observations, but I also have a few notes of my own to share.

I didn't expect to be in a room with 600 people. (You don't have to bust out your spreadsheet to immediately understand that Tufte is making some serious bank with these tours.) A room this size makes the presenter more remote in some ways---you know there is no hope of any sort of personal connection. This made it all the more interesting that Tufte started the day with a little speech about how presentation is a moral act and his philosophy as a presenter. I kinda liked this idea. For years, I included my philosophy of grading as part of a syllabus, but I admit that I never really talked with students about how I see my role as a teacher (or how they saw themselves as learners...let alone how we viewed one another). While he spoke, this video played on the screen:


A lovely visual to start the day.

The rest of the day was organized around various pieces of text from his books and other videos. Tufte is very anti-presentation software...and while he called out PowerPoint in particular, there was nothing in his comments that wouldn't have applied to Keynote or Prezi. His rejection was not so much about its misuse/abuse, but rather that paper is superior because it has a higher resolution than a screen and you can include more information in a smaller space. I agree---but I also think there is room for both. They have different purposes for communication.

One of the points Tufte made throughout the day is that the onus of understanding is on the viewer. I think this is an intriguing philosophy...one that seems at odds with one of the primary purposes of data visualization. I understand the reason behind making visualizations interactive and engaging for the audience, but unless you are certain about the level of data literacy they have, leaving interpretation completely open is asking for problems.

I was disappointed in a few parts of the "workshop." One was a 30-minute commercial for his other pursuits just before lunch and another was a 45-minute discussion of big data after lunch. I felt like the former was uncalled for (dude, you already have our money) and the second seemed out of place and a bit misguided (again, assuming that the audience for data is literate about research methodology and data in general).

Am I glad I went to the workshop? Yes---not so much for the information given, but because hearing from the original person about their own ideas provides a context you can't get anywhere else. Doesn't mean I liked or agreed with everything I heard, just that my understanding has been fleshed out. Would I go again? Probably not. Presentation quality was not good and nothing new was brought to the table. Perhaps he doesn't think he owes his audience the effort---people will buy his stuff and elevate his work regardless of what he does in a workshop. But I find that disappointing.

This experience didn't stop me from going to see another guru a couple of weeks ago: Stephen Few. More on that to come.