What approach should I use for remote testing?

There are really three big questions you need to answer when deciding how to set up an auditory experiment for remote data collection: what hardware will I use, what software will I use, and who are the subjects I want to test. In all three cases, the alternatives range from convenient and less controlled to more time consuming and well specified.

hardware: calibration & interfaces

  • loose control of auditory stimuli with respect to calibration & frequency response
  • flexible graphic and temporal specs
  • no “special” data collected (e.g., ambient noise levels)

Any user hardware

e.g., PC & headphones

or more controlled solutions (below)

  • stimulus level & frequency response defined within ~5 dB
  • controlled graphic and temporal specs
  • some specialized data collection capabilities (e.g., touch screen input)

specified hardware

e.g., iPad

or more controlled solution (below)

  • strict control of level and freq. response
  • other specialized measurement or interface required (e.g., calibrated ambient noise recordings, software permitting)

lab hardware

e.g., deliver tablet & sound level monitor

software: data handling and experimental control

  • standard procedures w/out modifications required

Preconfigured hearing research packages

e.g., PART

or more controlled solutions (below)

  • custom stimuli
  • standard interface and response sufficient

build-your-own systems

e.g., Gorilla

or more controlled solution (below)

  • custom procedures or real-time processing
  • non-standard interface or data collection (e.g., voice recordings, hardware permitting)

fully custom scripts

e.g., MATLAB or Python

subjects: demographics & instruction

  • anyone can participate
  • no one-on-one instruction required

anonymous & unsupervised

e.g., Mturk

or more controlled solutions (below)

  • targeted population
  • specialized instruction (e.g,. via zoom)

“by invitation” access

most hardware/software will work

  • populations requiring real-time supervision (e.g., children)
  • protocols requiring rigorous training

supervision by proxy (e.g., parent)

experimenter-administered protocol hybrid model (e.g., training in person, data collection at home)

most hardware/software will work