Abstract
Eye-tracking has become a valuable tool for studying cognitive processes in second language (L2) acquisition and bilingualism (Godfroid et al., 2024). While research-grade infrared eye-trackers are commonly used, there are a number of issues that limit its wide-spread adoption. Recently, consumer-based webcam eye-tracking has emerged as an attractive alternative, requiring only internet access and a personal webcam. However, webcam eye-tracking presents unique design and preprocessing challenges that must be addressed for valid results. To help researchers overcome these challenges, we developed a comprehensive tutorial focused on visual world webcam eye-tracking for L2 language research. Our guide will cover all key steps,from design to data preprocessing and analysis, where we highlight the R package webgazeR, which is open source and freely available for download and installation:https://github.com/jgeller112/webgazeR. We offer best practices for environmental conditions, participant instructions, and tips for designing visual world experiments with webcam eye-tracking. To demonstrate these steps, we analyze data collected through the Gorilla platform (Anwyl-Irvine et al., 2020) using a single word Span-ish visual world paradigm (VWP) and show competition within and between L2/L1.This tutorial aims to empower researchers by providing a step-by-step guide to successfully conduct visual world webcam-based eye-tracking studies. To follow along with this tutorial, please download the entire manuscript and its accompanying code with data from here: https://github.com/jgeller112/L2_VWP_Webcam