Tempe, AZ
Framework for Evaluating
City Employee Data Literacy
Data-driven decision making from government employees facilitates transparency, efficacy, efficiency, and citizen satisfaction. In the modern, digital world, the amount of data that can be collected, stored, and analyzed has exponentially increased. Recognizing this, the city of Tempe, Arizona has made it a priority to develop data literacy throughout its city workforce.
Previously, the Spring 2025 Paragon Policy Fellowship cohort partnered with the city of Tempe to develop a data literacy and ethics curriculum. Building on this effort, the Summer 2025 cohort has developed a municipal data landscape analysis, allowing the city of Tempe to gain insight into how its employees interact with and understand data.
The work conducted this summer aims to determine a framework, along with its tools and implementation strategy, necessary to classify employees’ data proficiency. By harnessing the developed framework, the city of Tempe can then collect the necessary information to effectively implement a comprehensive data governance strategy.
1. Literature Review: The methodology employed within this work began with a comprehensive literature review to identify existing data competencies employed throughout academia and industry, study case studies of other cities employing data governance strategies, and analyze existing literature competency assessments released online.
2. Stakeholder Engagement: A key part of the methodology used was actively engaging with key stakeholders throughout the project to ensure that the perspectives of those affected by the project or knowledgeable about the topic were heard. City of Tempe employees were interviewed to gain an understanding of how employees use data, think of data skills, and prioritize elements of data literacy. Academics familiar with data literacy were interviewed to understand how assessments or surveys could be best developed to assess competency.
3. Survey Development: The core of the developed framework consisted of a data literacy competency survey. The survey development process was completed by reading literature surrounding survey question development, analyzing the previously developed data curriculum’s content, referencing existing online assessments, and harnessing code to develop data visualizations and data sets.
Data Literacy Curriculum
While there is no established standard for data literacy competencies, a host of existing models were identified and analyzed through the literature review. In total, six data literacy competencies were identified in this work based on the synthesis of many of these models and competencies found throughout academia and industry:
a) Understanding Data
b) Collecting and Managing Data
c) Interpreting and Analyzing Data
d) Data Visualization
e) Data Ethics
f) Applying Data
Data Literacy Competency Means of Assessment
In order to assess the identified data literacy competencies, a survey was developed. This survey consisted of both a self-evaluation questionnaire, where respondents would rate their proficiency in various data skills, and an assessment where scenario-based questions were used to assess practical ability. By harnessing both internal and external methods of assessment, a more accurate snapshot of data literacy competency can be obtained.
Implementation Strategy
A vital step for the success of the municipal data landscape report survey is a carefully executed implementation strategy. This work provided clear steps for confirming the validity and reliability of the survey, moving forward with pilot programs, and distributing the survey to employees in an effective manner.
This project provides the tools necessary to gather critical insights into the data literacy proficiency of the Tempe, AZ workforce. The implementation of this work can provide the city with a descriptive overview of its employees’ ability to understand, collect, analyze, and interpret data while employing ethical, data-driven decision making. By harnessing this municipal data landscape analysis in addition to the previously developed data curriculum, Tempe will be primed to further implement data governance policy relevant to the needs of City employees and Tempe’s inhabitants.
The analysis provided gives key short-term, mid-term, and long-term steps for future work. These steps include guidance for the implementation of large-language models for assessment grading and suggestions for harmonization between the recently developed municipal data landscape analysis and the previously developed data literacy curriculum.
James Shin (Project Lead)
Georgia Tech
Angelly Cabrera
University of Southern California
Bhoomika Gupta
San Jose State University
Farhana Urni
Arizona State University
Nimra Arfi
Arizona State University
Sahasra Pechetty
Arizona State University