Is PsyNet right for me?

Online experiments are becoming an increasingly important tool in psychology, sociology, and economics research. They enable experimenters to recruit and test large and diverse participant groups in moments, thereby enabling experiment designs that would be almost impossible in the laboratory, ranging from simulated social networks to artificial music evolution to fine-grained perceptual mapping.

Nowadays there are many excellent platforms available for designing online experiments (e.g. Qualtrics, jsPsych, PsychoPy, Gorilla, PsiTurk, OpenSesame, Empirica, Dallinger, Breadboard, labJS, Labvanced, psychTestR, formr). The most appropriate platform depends on the individual research programme. Want simply to run participants through several surveys? Qualtrics will make this process very easy. Want to design a high-precision visual perception task? PsychoPy is a good bet. Want to contact the same participants repeatedly in a longitudinal design? formr has your back.

So, how to tell if PsyNet is the right tool for you? Ask yourself the following questions:

Do I want to design complex experiments?

  • e.g. designs that react to the decisions of the participant (iterated reproduction; Markov Chain Monte Carlo with People);

  • e.g. generating stimuli on the fly using Python;

  • e.g. recording audio or video from your participants that is analysed in real time on the web server.

Do I want to make efficient use of time and money?

  • collecting large amounts of data very quickly;

  • deploying different versions of the same experiment with minimal effort;

  • maximizing data quality and minimising wasted funds by automatically monitoring participant behaviour and ejecting poor participants.

Do I want an efficient programming experience?

  • programming complex experiments with a minimal amount of code.

  • leveraging large pre-existing libraries of prescreening tasks and experiment interfaces.

Do I believe in open science and open source software principles?

  • creating experiment implementations and libraries that are fully portable, shareable, and replicable;

  • avoiding expensive subscriptions to commercial software.

Do I have the right kind of technical skills/interest?

  • reasonably familiar with Python and Git (or willing to spend a few hours learning!);

  • willing to invest some time in learning how to write PsyNet experiment code.

If the answer to at least some of these questions is 'yes', we think you'd enjoy what PsyNet has to offer!