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This edition of Keeping Up With… was written by Diego Mendez-Carbajo.

Diego Mendez-Carbajo is Senior Economic Education Specialist at the Federal Reserve Bank of St. Louis, email: diego.mendez-carbajo@stls.frb.org

What is Economic Data Literacy?

Although a narrow definition of economic data literacy is not currently available, it can be outlined as the combination of specific expected competencies in economics and the broad data literacy needs of the workforce. [4] [5] Broadly defined, economic data literacy combines three sets of skills:

• Information Literacy, as defined by the Association of College and Research Libraries, is a set of abilities requiring individuals to “recognize when information is needed and have the ability to locate, evaluate, and use effectively the needed information.” [6]
• Numeracy, as defined by the National Numeracy Network, includes the “ability to communicate at a substantial level about quantitative issues in everyday life.” [7]
• Economic Analysis, as defined by the American Economic Association, involves the use of “theoretical models or empirical data” to study a very broad range of social questions. [8]

A Micro-Credential in Economic Data Literacy

The Library Services and the Economic Education team at the Federal Reserve Bank of St. Louis have developed a micro-credential program on economic data literacy for librarians. This free professional development program identifies seven foundational competencies, using FRED® data to provide opportunities for hands-on learning. [9]

Competencies

Saving Graphs and Downloading Data: Finding and visualizing the data you need for a project is time-consuming. Knowing how to save your work and selecting the format appropriate for your project will help you access, share, and make further use of your data.

Identifying Data Sources and Release Frequencies: Understanding how data are collected and revised is important to use them correctly. Also, the difference between open and proprietary sources determines how data can be redistributed. Knowing how to identify the open or proprietary character of a data source and how the data are collected, released, and revised will help you think critically about your data.

Understanding Data Types and Units: Understanding what the data represent and how that concept is measured is important to use them correctly. Also, identifying and understanding the units of measurement and the methodologies employed to estimate and report statistical observations will help you select the data appropriate to your purposes.

Visualizing Data: Creating data visualizations helps identify key takeaways in quantitative information. Data graphs are practical instruments of exploratory analysis showing trends, relative sizes, and correlations in data sets. Accurately designing and correctly interpreting data plots are preliminary steps for effectively communicating with data.

Storytelling with Data: Concisely describing data helps communicate the key features of quantitative information and connect those features to persuasive arguments. Clearly explaining what the data are and placing them in a relatable context make quantitative analysis accessible to diverse audiences.

Acting on Data: Making choices using quantitative information requires numeracy competencies and skills. Although those can be both very broad and very deep, a baseline competency conducting exploratory analysis using data visualizations provides a good foundation from where to undertake practical courses of action.

Using Data Ethically: Users of data must adopt ethical practices when gathering, analyzing, and sharing data. Unethical data practices undermine the end-uses of quantitative information. The principles of data ethics apply to all stages of data-related work, from collection to citation.

Learning by Doing

Each module first defines the targeted competency and its related skills. Next, librarians complete a knowledge check on the topic. Next, they acquire hands-on experience with FRED®, the largest online aggregator of U.S. economic data, by completing data search, graph building, and graph reading tasks. Next, both existing and newly acquired data literacy skills are demonstrated by analyzing two different realistic scenarios involving FRED® data. Last, librarians test their ability to transfer the demonstrated skills to a related task.

Visible Achievements

Each competency in the micro-credentialing course is matched to a digital badge issued by a third party. Librarians successfully completing individual course modules receive, at no cost, a badge certifying their achievement. Upon successfully completing all seven individual modules, librarians receive a digital certificate of achievement. All the digital badges can be shared through social media channels as well as directly emailed to current or potential employers.

Conclusion

Micro-credentials are truly authentic professional learning tools. Rather than asking learners to absorb information, micro-credentials present learners with dynamic opportunities to acquire and demonstrate their new or existing expertise. On the topic of economic data literacy, individual competencies can be stacked into an overall marker of achievement identifying the librarian as a skilled user and consumer of economic data.

Notes

[1] “Micro-Credentials,” National Education Association, Accessed February 18, 2022, .

[2] Ifenthaler, Dirk, Nicole Bellin-Mularski, and Dana-Kristin Mah, eds. Foundation of Digital Badges and Micro-Credentials : Demonstrating and Recognizing Knowledge and Competencies. Switzerland: Springer, 2016. .

[3] Gallagher, Sean. Educational Credentials Come of Age: A Survey on the Use and Value of Educational Credentials in Hiring. Boston, Massachusetts: Center for the Future of Higher Education and Talent Strategy, Northeastern University, 2018. .

[4] Pothier, Wendy G., and Patricia B. Condon, “Towards Data Literacy Competencies: Business Students, Workforce Needs, and the Role of the Librarian,” Journal of Business and Finance Librarianship 25:3-4, 123-146 (2020), .

[5] Mendez-Carbajo, Diego, “Baseline Competency and Student Self-efficacy in Data Literacy: Evidence from an Online Module,” Journal of Business and Finance Librarianship 25:3-4, 230-243 (2020), .

[6] Association of College and Research Libraries, “Framework for Information Literacy for Higher Education,” Accessed February 18, 2022, .

[7] National Numeracy Network, “What is Numeracy?” Accessed February 18, 2022, .

[8] American Economic Association, “What is Economics? Understanding the Discipline,” Accessed February 18, 2022, .

[9] Research Information Services, Federal Reserve Bank of St. Louis, “Data Literacy for Librarians,” Accessed February 18, 2022, /.