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A primer on running human behavioural experiments online.

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Online experiments enable large-scale behavioral data collection. This guide offers a broad introduction to online testing tools and infrastructure, facilitating rapid hypothesis to data translation.

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Area of Science:

  • Behavioral Science
  • Psychology
  • Human-Computer Interaction

Background:

  • Traditional lab-based experiments have limitations in scale and reach.
  • Online environments offer unprecedented potential for collecting large-scale behavioral data.
  • Transitioning to online research requires understanding new tools and methodologies.

Purpose of the Study:

  • To provide a high-level overview of online testing infrastructure.
  • To introduce researchers to the fundamental concepts of conducting experiments online.
  • To bridge the gap between existing platform-specific tutorials and a general understanding of online research.

Main Methods:

  • Literature review of online experiment platforms and tools.
  • Conceptual framework development for online behavioral data collection.
  • Synthesis of common terminologies and infrastructure components.

Main Results:

  • Online experiments allow for rapid recruitment of thousands of participants.
  • Familiarization with online tools enables swift transition from hypothesis to data.
  • A broad understanding of online testing infrastructure is crucial for effective implementation.

Conclusions:

  • Online testing significantly enhances the scalability and efficiency of behavioral research.
  • This paper serves as a foundational guide for researchers new to online experimentation.
  • Adopting online methodologies can accelerate the pace of scientific discovery.