Resources

In this paper, authors invite the human factors and ergonomics community to engage with election administration research. The paper describes the complexity and scale of U.S. election administration and identifies open research challenges where human factors expertise is directly applicable, including accessible design, poll worker training, and error minimization.

This report is a comprehensive reference for election officials on election processes and best practices, including guidance on physical security and location management for polling places. It serves as the primary federal-level guidance on polling place operations in the absence of national layout standards.

This publicly available interactive tool (currently in beta) allows election officials to map the layout and setup of voting equipment at an in-person polling location. Users can generate a custom, to-scale model of their space, incorporate key elements such as electrical outlets, doors, and windows, or select from common layout designs. Designs can be printed and shared with polling location leads to facilitate setup.

In this report, authors analyze evidence on voting difficulties, potential solutions, and ideas for a new center - the Center on Disability and Voting - from data using surveys, focus groups, and interviews with key stakeholders.

The biennial comprehensive survey of election administration across all 50 states, five territories, and D.C., covering the 2024 presidential general election, achieved a 100% response rate. Key in-person voting findings include: more than 70% of voters cast ballots in person, split roughly evenly between Election Day and early in-person voting; mail ballot use declined to approximately 30%, down from 43% in 2020; more than 770,000 individuals served as poll workers; all states reported offering some form of in-person voting before Election Day; and ballot drop box use increased by nearly 10 percentage points from 2022 to 2024 in states that offered them. Two-thirds of voters cast ballots in person, reflecting a significant post-pandemic return to in-person voting. The survey also covers voter registration, UOCAVA voting, absentee voting, provisional balloting, and voting technology.

This toolkit provides signage guidelines and ready-to-use templates designed for election offices of any size. They include directional signs, accessibility notices, and voter instruction materials for both inside and outside the polling location.

This is a publicly available training module that helps election jurisdictions build data skills through hands-on R exercises. The program shows election offices how to transform operational data into actionable decisions, such as improving staffing, resource allocation, and the overall voting experience.

This report details how American voters experienced the 2024 general election. It is based on a survey of 10,200 registered voters, including 200 from each state plus D.C. Key findings from in-person voting include: over 70% of voters voted in person; mail-in voting decreased to 29% from 43% in 2020; wait times for voting were mostly short, but some disparities remained; and public schools saw a decline as polling locations, with community centers becoming the most common alternative.

This paper synthesizes best practices for in-person voting across polling place access, check-in and wait times, polling place layout and design, ballot design, and the voter experience.

This report provides a comprehensive update to the EAC's landmark poll worker reports from 2007 and 2016, based on current data across four key areas: recruitment, training, retention, and evaluation. It captures the significantly transformed landscape of poll worker management since 2020, addressing new challenges like workforce shortages, threats against election workers, and the adoption of emerging technologies. The report also highlights state-by-state practices and emerging best practices from jurisdictions nationwide.

This publicly available tool allows election offices to enter the quantities of equipment, materials, and archives they have and receive an estimate of the warehouse space required to store in-person voting materials.

In this PhD dissertation, Houghton develops advanced algorithmic methods to model voter arrival behavior and vote center utilization to support election resource and capacity planning. Three core contributions: (1) compares voters’ demographic characteristics across three vote center types during the 11-day voting period across multiple elections; (2) analyzes how voters choose among multiple available vote center locations by using graph-based methods to analyze network data and perform statistical community detection; and (3) uses spatial access metrics as input to a genetic algorithm to optimize location selection for vote center siting decisions.