4.5 Article

Gorilla in our midst: An online behavioral experiment builder

期刊

BEHAVIOR RESEARCH METHODS
卷 52, 期 1, 页码 388-407

出版社

SPRINGER
DOI: 10.3758/s13428-019-01237-x

关键词

Online methods; Remote testing; Browser timing; Attentional control; Online research; Timing accuracy

资金

  1. Economic and Social Research Council (ESRC) [13115739]
  2. Templeton World Charity Foundation
  3. Medical Research Council [0159]
  4. ESRC
  5. MRC [MC_UU_00005/2, MC_UP_A060_1103] Funding Source: UKRI

向作者/读者索取更多资源

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.

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