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Behavior Research Methods· 2019Q1

Gorilla in our midst: An online behavioral experiment builder

Alexander Leslie Anwyl-Irvine, Jessica Massonnié, Adam Flitton, Natasha Z. Kirkham et al.

Short summary

The Gorilla Experiment Builder is a new platform designed to lower technical barriers for online behavioral research, enabling researchers to create and deploy reaction-time-sensitive experiments without extensive programming knowledge.

AI-generated from the title and abstract; the full text is not read.

Key points

  • The Gorilla Experiment Builder simplifies online experiment creation, reducing the need for programming skills like JavaScript.
  • It aims to resolve timing issues crucial for reaction-time-sensitive measures in online research.
  • The platform successfully replicated a 'conflict network' effect in reaction-time tasks across varied participant groups and settings.
  • It supports scalable research with diverse participant demographics and equipment.

AI-generated from the title and abstract; the full text is not read.

Abstract

Behavioral 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 behavioral research, as well as 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. To demonstrate the platform's aptitude for accessible, reliable, and scalable research, we administered a task with a range of participant groups (primary school children and adults), settings (without supervision, at home, and under supervision, in both schools and public engagement events), equipment (participant's own computer, computer supplied by the researcher), and connection types (personal internet connection, mobile phone 3G/4G). We used a simplified flanker task taken from the attentional network 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.

The authors' abstract, as published at the source. Behavior Research Methods, 2019 · DOI ↗

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Field: Computer Science Applications

Computer Science ApplicationsComputer Science