TY - JOUR T1 - Gorilla in our Midst: An online behavioral experiment builder JF - bioRxiv DO - 10.1101/438242 SP - 438242 AU - Alexander Anwyl-Irvine AU - Jessica Massonnié AU - Adam Flitton AU - Natasha Kirkham AU - Jo Evershed Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/02/25/438242.abstract N2 - Behavioural researchers are increasingly conducting their studies online to gain access to large and diverse samples that would be difficult to get in a laboratory environment. However, there are technical access barriers to building experiments online, and web-browsers can present problems for consistent timing – an important issue with reaction time-sensitive measures. For example, to ensure accuracy and test-retest reliability in presentation and response recording, experimenters need a working knowledge of programming languages such as JavaScript. We review some of the previous and current tools for online behavioural research, and how well they address the issues of usability and timing. We then present The Gorilla Experiment Builder (gorilla.sc) a fully tooled experiment authoring and deployment platform, designed to resolve many timing issues, and make reliable online experimentation open and accessible to a wider range of technical abilities. In order to demonstrate the platform’s aptitude for accessible, reliable and scalable research, we administered the task with a range of participant groups (primary school children and adults), settings (without supervision, at home, and under supervision, in schools and public engagement events), equipment (own computers, computer supplied by researcher), and connection types (personal internet connection, mobile phone 3G/4G). We used a simplified flanker task, taken from the Attentional Networks Task (Rueda, Posner, & Rothbart, 2004). We replicated the ‘conflict network’ effect in all these populations, demonstrating the platform’s capability to run reaction time-sensitive experiments. Unresolved limitations of running experiments online are then discussed, along with potential solutions, and some future features of the platform. ER -