Many areas in the language sciences rely on collecting data from human participants, from grammaticality judgments to behavioural responses (key presses, mouse clicks, spoken responses). While data collection traditionally takes place face-to-face, recent years have seen an explosion in the use of online data collection: participants take part remotely, providing responses through a survey tool or custom experimental software running in their web browser, with surveys or experiments often being advertised on crowdsourcing websites like Amazon Mechanical Turk (MTurk) or Prolific. Online methods potentially allow rapid and low-effort collection of large samples, and are particularly useful in situations where face-to-face data collection is not possible (e.g. during a pandemic); however, building and running these experiments poses challenges that differ from lab-based methods.

This course, developed by Prof Kenny Smith, from the School of Philosophy, Psychology and Language Sciences, provides a rapid tour of online experimental methods in the language sciences, covering a range of paradigms, from survey-like responses (e.g. as required for grammaticality judgments) through more standard psycholinguistic methods (button presses, mouse clicks) up to more ambitious and challenging techniques (e.g. voice recording, real-time interaction, iterated learning).  These course materials, which include weekly readings and programming tasks, also explore the main platforms for reaching paid participants, e.g. MTurk and Prolific, and discuss some of the challenges around data quality and ethics.

The course materials are released under a CC BY licence and are available on Github: Online Experiments for Language Scientists.

Header image by xresch from Pixabay