Improving data literacy in your team using Bloom's taxonomy: A practical approach from Coalesce 2023

"Why would we expect our business stakeholders to be able to evaluate the difference between good questions and weird ones if they don't have any baseline knowledge of the data? We're asking them to jump too high."

Faith Lierheimer, Data Analyst at Parsyl, explains how to improve data literacy in organizations using a teaching tool, Bloom’s taxonomy. She also shares her experiences and strategies for facilitating a better understanding of data among stakeholders.

Bloom’s taxonomy is a tool that breaks learning complex topics down into manageable steps

Faith believes that data practitioners should think like teachers when helping others learn about data. She elaborates, “I think that you should think like a teacher. Teachers think a lot about how people learn and how best to communicate information. And the study of these concepts is called pedagogy.” Then she introduces the concept of Bloom’s taxonomy, a pedagogical framework that helps people learn by considering the complexity of the information they’re learning. “There’s lots of pedagogical tools out there. The one that I’m going to tell you about today is called Bloom’s Taxonomy… Bloom's taxonomy is really helpful in breaking down the process of understanding new concepts into discrete, manageable steps.”

Enhancing data literacy is key for effective business-stakeholder interactions

Faith discusses the importance of data literacy for business stakeholders, stressing that comprehension and understanding of data are crucial for making informed decisions. She uses examples from her experience to illustrate common challenges in business-stakeholder interactions, such as vague requests and inaccurate assumptions about data.

After sharing some of her first-hand experiences with stakeholders, Faith explains, "Both of [the examples] display a lack of data understanding from my stakeholders." She proposes that stakeholders can better comprehend how data impacts their projects by thinking like a teacher and using Bloom's taxonomy to break down the process of understanding new concepts.

She elaborates, “If your business stakeholders understood your data a little bit better, they might ask better questions and participate more fully in their own projects.” She also emphasizes the need to build data literacy step-by-step, starting with the basics, to enable stakeholders to ask better questions.

The role of "knowledge building" activities for data literacy

Faith proposes the idea of "knowledge building" activities to improve data literacy among stakeholders. She distinguishes between passive and active methods, recommending a combination of both to facilitate better understanding. Passive methods include cataloging data, while active methods involve engaging stakeholders in games and discussions.

Faith shares an example of an unstructured knowledge-building activity called "Look Olympics" that she conducted at her previous job: "The gold medal emoji is a friendly competition for the top Looker user of the week, and I simply did that by number of queries run." She also suggests structured, knowledge-building activities such as lunch-and-learns for more in-depth understanding.

She notes, “The point was to have our co-workers walk away understanding these four topics and these four topics only. We're not expecting them to become experts. This is just the baseline knowledge that we decided was important for them to know."

Ongoing comprehension assessments are essential for effective data literacy

Faith stresses the importance of ongoing comprehension assessments to gauge stakeholders’ understanding of data. She suggests "coffee and comprehension" interviews to measure this and encourage a better understanding of data among stakeholders.

She says, "Data literacy can only bloom through small steps, so stay persistent and stay patient." Faith emphasizes that improving data literacy is a long-term process and patience and persistence are key to your success.

Faith’s key insights on boosting data literacy

• Data literacy is crucial for businesses and stakeholders to make informed decisions
• Bloom's taxonomy, a pedagogical tool, can be used to improve data literacy. It breaks down the process of understanding new concepts into manageable steps
• Passive and active knowledge-building opportunities can be created to improve data literacy
• Comprehension interviews can be used to assess stakeholders' understanding of data
• Demonstrating potential applications of data can help stakeholders understand its importance and how it can be used