Data Storytelling
Ed Direction Data Fellows: Asynchronous Module
July 2022
Embedded Files
Welcome to the Data Storytelling Optional Asynchronous Module.
You will work through this module by scrolling through this learning space. To expand documents and slide decks that are included, you can click on the gray arrow at the top right corner of each item.
Feel free to focus on the pieces of this module that are most relevant to your topics of interest.
Please complete the Exit Ticket at the end of the module. We will use your submission to track completion.
Please contact datafellows@eddirection.org if help is needed.
Click on the button to the left to open the note-catcher, which is mirrored to follow the content as it is presented on the Learning Space. As you navigate through this module, you are welcome to use this optional tool to capture your notes.
Refer to your note-catcher each time you see this icon.
Session Outcome: This optional asynchronous module will strengthen Data Fellows' ability to craft and deliver compelling RSSP data stories to LEA stakeholders.
Success Criteria: By the end of the session, Data Fellows will be able to...
Understand how to use data to tell stories
Utilize dashboard visualizations as story-telling aides.
See It: TEA STAAR Results Summary (10 Min)
See It: TEA STAAR Results Summary (10 Min)
2022-staar-results-summary.pdfTEA Recently released the summary of the 2022 STAAR Results. Read through the slide deck and reflect on the following questions using the note-catcher.
What storytelling techniques did TEA use while presenting their data?
Which parts of the narrative were most easy to follow?
Is there anything you would add or take away if you were responsible for crafting a story using this information?
Name It Part 1: Data Storytelling (An Overview)
Name It Part 1: Data Storytelling (An Overview)
Why Data Story-Telling
Telling well-crafted stories is one of the most effective forms of communication. Vanessa Boris, a senior manager at Harvard Business Publishing Corporate Learning, describes that
“Good stories do more than create a sense of connection. They build familiarity and trust, and allow the listener to enter the story where they are, making them more open to learning. Good stories can contain multiple meanings so they’re surprisingly economical in conveying complex ideas in graspable ways. And stories are more engaging than a dry recitation of data points or a discussion of abstract ideas.”
She goes on to explain that
“Storytelling also helps with learning because stories are easy to remember. Organizational psychologist Peg Neuhauser found that learning which stems from a well-told story is remembered more accurately, and for far longer, than learning derived from facts and figures. Similarly, psychologist Jerome Bruner’s research suggests that facts are 20 times more likely to be remembered if they’re part of a story.”
Using well-crafted stories to convey your data is more engaging and memorable than simply sharing disparate and disconnected facts and figures. Harnessing this skill is especially important when building your dashboard. According to one study of private organizations, although 82% of companies indicated they used dashboards to share data with colleagues at every level of the organization, 53% of survey respondents described that their company's dashboards were consistently ignored because they were too complex to interpret. Of those 53%, over half indicated that the dashboards were unintelligible because the visualizations lacked sufficient context.
Take a look at this example of a poorly designed dashboard from a non-education context.
If you are like most people, this dashboard is difficult to interpret because there is little context for each visualization, and it is not immediately clear how the visualizations work together to tell a compelling story.
What is Data Story-Telling?
In her Harvard Business Insights article Data Storytelling: How to Effectively Tell a story with Data, Catherine Cote describes that data story-telling is “the ability to effectively communicate insights from a dataset using narratives and visualizations.” That definition can be expanded to include the ability to discern and convey a through-line in the data that resonates with your audience and inspires them to change their behavior.
Within the context of your work as a Data Fellow, data story-telling includes being able to effectively use your data dashboard to tell the story of what is happening within your district as the RSSP team implements targeted interventions to improve student learning.
This process will require you to sort through large amounts of data and determine which data is worth sharing and which data is not worth sharing. When making these decisions, it is essential that you create transparency with your RSSP team. Explaining the rationale for why we have chosen to prioritize some data over others helps guard against implicit biases.
Stop and Think: Which points during the RSSP Improvement Cycle create natural opportunities to share data stories with your RSSP team?
Name It Part 2: Data Story-Telling (A Guide)
Name It Part 2: Data Story-Telling (A Guide)
In his Harvard Business Review video, Scott Berinato introduces a compelling framework for how to develop narratives around complex data. Enjoy!
The Guide
Below is a step by step guide anchored around Berinato’s framework (and accompanied by insights from other scholars and professionals), for how to create a data story from the RSSP data you are collecting.
As you read through the guide, please note that you will be telling multiple data stories throughout your time as a Data Fellow. As you read through the following steps, reflect on how you can embed this framework into the ongoing progress monitoring happening within each stage of the RSSP process.
Step 1: Collect the data
This is (intuitively) the first step. Developing a strong analysis and measurement plan centered around RSSP priorities is the foundation upon which the rest of your data story rests. If you do not have the right kinds of data or your data are not accurate, your story will ultimately fall flat.
Step 2: Analyze the data.
Using descriptive and exploratory analysis (see webinar 8) you can begin to uncover patterns and relationships in your data between student performance, student characteristics, and district implementation efforts.
To recap an important point from webinar 8, we can uncover relationships between variables in our datasets through correlation. When we use correlation, we are examining the covariance -- or co-movement -- between variables.
For example, if we wanted to see if there was a relationship between student test scores and the implementation of HQIM, we would look at the extent to which test scores increased as the implementation of HQIM increased.
It is important to stress that at this level, we are not able to determine if there is a causal relationship between two variables (i.e. implementing HQIM caused test scores to increase). There could be a variety of other factors that caused test scores to rise, and running a simple correlation between HQIM implementation and test scores does not enable us to rule out those other factors. It does, however, allow us to say that there appears to be a relationship between HQIM implementation and test scores, and the strength of that relationship is indicated by the correlation coefficient (the value ranging from -1 to 1).
Being precise in our description of what the data is saying and what the data is not saying is essential. Imprecision in our descriptions can lead our audiences to draw conclusions that may not actually be true.
Step 3: Avoid Biases
Miro Kazakoff, a lecture at MIT’s Sloan School of Management, describes that
“Proficiency with data storytelling means being able to present information without injecting bias... This requires effective data storytellers to be ruthless editors and [avoid] the tendency to adjust data to fit preexisting story lines.”
At times we all may feel the urge to make our data appear more definitive than they actually are in order to provide evidence to justify an initiative in which we believe. The best analysts resist this temptation. They instead use precise language to describe what the data are saying and what the data are not saying.
Step 4: Develop the Narrative
As demonstrated by Berinato, the narrative within your data story has three components: Setup, Conflict, and Resolution
Setup: The “before” state of the data.
What was the status quo before a change happened or a new initiative began? In your context as a Data Fellow, the setup could look like any of the following:
The state of student learning
Before the pandemic
Prior to your LEA’s implementation of RSSP
After year one of RSSP implementation
The status of implementation and performance data prior to
The Mid-Cycle Stepback
Improvement Cycle 1 Review
Conflict: How has the data changed?
Did the state of the data featured in the set up change gradually or drastically?
Are there any data that help explain the why behind the change?
In your context as a Data Fellow, the conflict might be the change (or lack of change) in implementation and performance data after
The pandemic began
Your LEA’s implementation of RSSP
Year one of RSSP implementation
The Mid-Cycle Stepback was completed
Improvement Cycle 1 Review concluded
Resolution: The “after state” that the change leads to.
What are the implications of the new reality?
In your context as a Data Fellow, the “resolution” will most likely relate to the present conditions of your LEA and the implications of those present conditions.
Examples of what the “resolutions” could look like are
Implementation and performance metrics are both improving
Implementation metrics are improving but performance metrics are not
Implementation metrics are not improving but performance metrics are
Both implementation and performance metrics are not improving
The “resolution” will help determine what your district’s next steps should be. If student outcomes are increasing and are correlated with improved implementation efforts, then that provides some evidence that your LEA should maintain its current efforts. If student outcomes are stagnant or decreasing, then that indicates a change of course is potentially needed.
Based on your individual circumstances and the phase of RSSP Improvement Cycle your LEA is in, there are a variety of “setups, conflicts, and resolutions” you could feature as a part of the data stories you are constructing.
You will have many opportunities to share data stories throughout the RSSP process, and each story will have its own unique elements and nuances. The story you craft at the Mid-Cycle Stepback may look radically different than the story you crafted at the beginning of the year. It is essential that we diligently work to describe the data as accurately as possible as it continually changes throughout the year.
Step 5: Design the Visuals
Your primary goal when using your dashboard to tell a data story is to have the narrative be self-evident. The story should tell itself via the titles, text boxes, and visualizations. If you find yourself having to explain the story to those who have access to your dashboard, that’s an indication that your dashboard needs some work. The following best practices are fantastic starting points to consider when designing your dashboard as a story-telling aid.
Organize Sections
When designing your dashboard, you have significant flexibility in how you organize your visualizations. Creating intuitive sections that help your audience naturally follow the throughline of your plot increases the chances your dashboard will leave a lasting impact on those who view it.
Those sections could directly follow the “setup” “conflict” “resolution” structure introduced by Berinato. Or they could be divided into different data stories -- a story for third grade reading, a story for fourth grade math, etc.
Regardless of how you organize the sections within your dashboard, ensure that they are logical and intuitive.
Reduce the Noise
It is highly unlikely that all of the data you collect will fit within the specific story you are trying to tell. If there is a relationship between the implementation of your district’s RSSP strategy and student outcomes, focus on including only the most relevant variables within the visualizations.
If student attendance rates are not affecting your implementation or performance data, then it can be smart to not include them on your dashboard (unless specifically directed to by your RSSP team).
By removing the data from your dashboard that does not directly help tell the story you are crafting, you make it easier for your audience to follow the narrative embedded within the data dashboard.
Use Descriptive Titles
Writing descriptive titles for each visualization will provide a key support for your audience as they work to understand the data story.
Strike a balance between descriptiveness and brevity. Titles for visualizations on dashboards shouldn’t be more than a few words, but there is tremendous potential for guiding your audience through your narrative one title at a time.
You might consider reading the titles of your visualizations sequentially, as if you are reading a small picture book. Doing so could help you streamline the text of your narrative.
Provide Context
One of the key challenges of telling a data story -- especially via a dashboard -- is that you do not know the context each member of your audience has prior to hearing the story. The superintendent of your district is going to have access to and familiarity with different types of data than a principal of a school will. Each audience member will need different pieces of context in order for them to fully understand the visualizations and insights embedded within your dashboard.
You will need to strike a balance between providing enough context so that everyone at every level of the LEA will be able to understand what each visualization in your dashboard is saying without being overly descriptive.
Successfully providing context without being overly descriptive is as much of an art as it is a science. The best way to refine that skillset is to design dashboards, have people at every level of the LEA read it, solicit feedback from them, create a new iteration of the dashboard, and repeat the process. Going through a few feedback cycles will help you hone in on exactly the right amount of context to provide.
Do It: Tell Your RSSP Data Story
Do It: Tell Your RSSP Data Story
It’s time to put together your learning from this asynchronous session by applying it to your own RSSP context. Please navigate to the Do It section of your note-catcher and complete the corresponding activity.
Completing this activity will help you exercise the skills required to effectively communicate the story of your LEA’s RSSP data.
Module Complete!
Module Complete!
Congratulations on completing the Data Storytelling module. Please complete the Exit Ticket form by clicking on the link below. We will use the information you submit to track your completion.
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