Introducing the Eye Tracking Preregistration Template: Q&A with Libby Jenke and Nicolette Sullivan

Eye tracking is used across a broad range of disciplines—from psychology and neuroscience to marketing, political science, and communication—to capture real-time measures of attention and decision-making. Yet the method comes with a distinct layer of technical infrastructure that is often underreported and not fully captured in other preregistration templates. Choices related to calibration procedures, preprocessing algorithms, and other parameters can meaningfully shape the data collected and the conclusions drawn, but are often missing from preregistrations that focus primarily on behavioral analyses—making it difficult for others to understand what was actually done or to reproduce the results.

Libby Jenke and Nicolette Sullivan developed the Eye Tracking Preregistration Template to fill that gap. Now available on the Open Science Framework (OSF), the Eye Tracking template guides researchers through the technical decisions that precede data collection in eye tracking studies—making those choices visible before a single data point is recorded.

Jenke is an Assistant Professor of Political Science at the University of Houston, whose work uses eye tracking to obtain direct measures of decision-making processes, information acquisition, and attention. Sullivan is an Assistant Professor of Marketing at the London School of Economics and Political Science, where her research draws on eye tracking, drift diffusion modeling, and neuroimaging to examine how attention shapes consumer choice.

In this Q&A, Jenke and Sullivan discuss what inspired the development of the template, how it addresses the underreporting of key technical decisions in eye tracking research, and how it helps researchers across a range of disciplines think through key study design decisions.

Q: What motivated you to develop the Eye Tracking Preregistration Template?

A: Eye tracking has a lot of moving parts that researchers have to get right before they ever collect a single data point; the calibration setup, the construction of areas of interest, the preprocessing algorithms should all be specified in advance. We kept noticing, in reviewing papers and in our own work, that critical decisions about these elements were underreported or unreported, and typically didn’t make it into pre-registrations that focused on behavioral analyses. That makes it very hard for a reader to understand what was actually done, let alone replicate it.

Q: What specific challenges in eye tracking research does this template aim to address?

A: Eye tracking software comes with default settings---minimum fixation duration and velocity thresholds---and researchers often accept those defaults without reporting them or necessarily understanding what they're doing to the data. Our template requires researchers to specify and justify those choices in advance. That's not just good for transparency; it's good for the research itself.

Q: How does this template differ from more general preregistration templates, and what makes it uniquely suited for eye tracking research?

A: General preregistration templates are excellent but are focused on behavioral measures. For example, they ask about your hypotheses, sample size, analysis plan. However, eye tracking has a whole layer of infrastructure that general templates don't touch: How was the eye tracker calibrated? How were the areas of interest constructed and sized? What gap-fill algorithms were used? What was the minimum fixation duration? These can affect the data you collect and the inferences you draw. This template makes them integral to the preregistration. In doing so, we hope to increase transparency as well as researchers’ consideration of these sometimes-hidden parameters.

Q: How does the template guide researchers in practice when planning and documenting their studies?

A: Filling it out forces decisions that researchers might otherwise defer until the data are in front of them, and at that point it's much harder to make those decisions without being influenced by what the data indicate. For instance, specifying in advance exactly how you will construct your areas of interest, and what the exclusion criteria for individual trials will be, protects you from unconsciously adjusting those choices to produce a cleaner result. The template makes the reasoning visible before the data are collected.

Q: Who do you envision using this template, and how might it help shape research practices in eye tracking?

A: Researchers across a wide range of disciplines (e.g., psychology, marketing, political science, neuroscience, communication, public administration) are now using eye tracking, often without a dedicated methodologist with prior training. Early career researchers especially benefit from having a structured document that surfaces decisions they might not even know they need to make yet. We hope it functions a bit like a checklist in that sense: not as a bureaucratic exercise, but as a genuine thinking tool.

Q: Looking ahead, what impact do you hope this template will have on transparency, reproducibility, and comparability in eye tracking research?

A: Broadly, we hope it contributes to a culture in which the planning of a study is treated as seriously as the reporting of its results. The decisions that get made before data collection (what to measure, how to measure it, what counts as a usable trial) are consequential. The template is an argument, in document form, that those decisions deserve the same rigor and transparency as behavioral analyses.