Best Practices

Data Literacy in Early Childhood Education: Not an Island Unto Itself

Read Time: 5 minutes
Nicol Russell, Ed.D.
Vice President, Implementation Research, Teaching Strategies
April 27, 2020

As an early childhood education professional, I’ve often thought about the phrase “no man is an island,” and find it applicable to so many parts of our work. This phrase comes from one of the most memorable books I’ve ever read, Devotions Upon Emergent Occasions, a collection of essays by English poet John Donne. He was talking about the interconnectedness of humankind and the idea that man’s survival is dependent on community. This idea reminds me of data literacy and the data systems that drive our daily work.

The Harvard Business Review (HBR) published this article on improving your team’s data literacy, which is the ability to obtain and understand meaningful information from data. While the article is about businesses’ use of data, I gathered three main points that relate to early childhood education leadership and data literacy:

Data literacy is a leader’s responsibility but requires a team effort.

If your goal is to build a culture of successful data collection, analysis, and use, everyone in your program has to be data-literate. This doesn’t mean everyone needs to have the technical skills to build a data system, but it does mean that everyone who is collecting data understands the why, what, and how of the data collection. For example, if you are using a child outcomes assessment tool like Teaching Strategies GOLD as a metric for tracking your program’s school-readiness goals, teachers should understand that it is an assessment tool (not a curriculum) and that it is designed to help them both understand children in their classroom and reflect on their teaching practices.

As a leader, it is your responsibility to provide your teachers with that information. Review the functions and features of the tools your program uses, and ensure your staff can perform the necessary tasks to obtain the usable data. Also be sure to set your program up for success. Share what success looks like for all involved. Define the steps and process for collecting, analyzing and sharing data. This will support better decision-making and an increase in their confidence with data.

Data literacy is a relationship between the technical and non-technical.

In the HBR article, the authors conducted a survey of businesses and found that while companies found their staff technically capable, they were lacking non-technical skills. Such as, asking the right questions, understanding which data is relevant, interpreting the data so the results would be meaningful, and telling their stories with data visualizations.

In early childhood, the data issues are similar: many programs that are funded by state or federal programs require data reporting for accountability measures. This accountability often leads to the unintended consequence of a heavy focus on the technical components of data collection such as setting goals, selecting tools, and reporting results. Strong data literacy involves supporting non-technical skills, understanding the context in which data is collected, and responding to all the contributing factors of any result.

For many programs, this means partnering with a trusted third party to provide external support to help them understand how to collect and use data. For other programs, this may mean developing internal capacity to do rich data exploration.

Data literacy is not just the technical parts of a system, or the “whats.” It’s also about the non-technical parts: the “whys” and “hows.” When we understand the interdependency of the technical and non-technical parts, we move towards true data literacy.

Data literacy is absolutely achievable.

We have been talking about data and how it should inform curriculum, programs, and quality improvement for so long that it may sometimes seem like it is impossible to do all the necessary things for good data practices, but it is an achievable goal.

Here are two simple tips for making it happen:

  • Start with “why.” State or federal mandates are important, but they shouldn’t be your sole reason for data collection. It’s the equivalent to the old parenting “because I said so.” Instead, use your vision to inform your data practices. Ask yourself: What data do we need to help us do right by children and families? Where can we get that data?
  • Focus on meaning-making. Once you’ve established your “why,” consider how you build a culture around it. It’s what you do to data, with data, and about data that becomes your data culture. Ask yourself: What is this data telling us about ourselves? What is it telling us about what we are doing for children and families? How can we do that better?

When John Donne was meditating on his beliefs about life and the universe in the 17th century, I’m sure he wasn’t thinking data and early learning programs. But, what a nod to his brilliance that here we are, in the 21st century, willing to recognize that data is not an island unto itself! It requires team support and non-technical skills to be truly achievable.

No matter your needs, we are committed to supporting you as a leader. We have a team of knowledgeable staff who are dedicated to our mission of helping educators feel empowered and inspired as they teach and care for our youngest learners.

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