Computer mediated communication (CMC) is a growing trend in our globalized world, facilitated by social media network tools such as Facebook and Twitter, and messaging apps such as Skype, WhatsApp, and Line. Much of this communication occurs in a second language (L2), but little is known about if and how CMC facilitates Second Language Acquisition (SLA). One window into attentional processes during CMC that might support SLA can be gained through the use of eye tracking methodology. Eye-trackers allow a researcher to identify the focus of attention and can reveal the linguistic information that a learner fixates on during chat sessions. Eye-trackers can also uncover what prompts L2 users attend to as they generate output text, such as the task input (e.g., picture, instruction, website), their partner's chat text, or the chat log of their current conversation.
In this presentation, we will introduce a new software tool that can facilitate research on eye-tracked CMC. Our EyeChat tool is a single-file, multiplatform tool that continuously monitors all text fixated on by the user in a custom chat window, prompt screen, or web browser interface. First, we will explain the motivation for the software development and then briefly review the software and demonstrate its core functionality. Next, we will describe an experiment that explores the utility of the tool in a research project on L2 learners' CMC interactions. Finally, we will discuss further applications of the software and new features that we plan to add in the near future.