PsychoPy: Difference between revisions
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The following two lectures provide a very basic introduction into [https://psychopy.org/ PsychoPy], an open-source cross-platform package allowing you to run a wide range of experiments in the behavioural sciences. The [[Media:PsychoPy1.pdf|first lecture]] provides an overview over PsychoPy and its graphical user interface, introduces several components that can be used to generate experiments (e.g., presenting text or sounds and obtaining feedback from the keyboard), how those can be combined into routines and ran several times using loops. It finally prepares you for the assignment to create a questionnaire yourself.<br> | |||
[[ | The [[Media:PsychoPy2.pdf|second lecture]] briefly introduces how to run experiments generated locally (on your own machine) as online experiments, how to evaluate data obtained from experiments in PsychoPy, and ends with discussing several considerations when preparing experiments such as randomization, types of stimuli (and how to prepare them), as well as tasks for the participants. | ||
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On the PsychoPy web page, there is a wealth of further [https://workshops.psychopy.org/teaching/index.html resources for teaching and learning] to extend what is covered in the two lectures above. | |||
Latest revision as of 11:15, 7 February 2023
The following two lectures provide a very basic introduction into PsychoPy, an open-source cross-platform package allowing you to run a wide range of experiments in the behavioural sciences. The first lecture provides an overview over PsychoPy and its graphical user interface, introduces several components that can be used to generate experiments (e.g., presenting text or sounds and obtaining feedback from the keyboard), how those can be combined into routines and ran several times using loops. It finally prepares you for the assignment to create a questionnaire yourself.
The second lecture briefly introduces how to run experiments generated locally (on your own machine) as online experiments, how to evaluate data obtained from experiments in PsychoPy, and ends with discussing several considerations when preparing experiments such as randomization, types of stimuli (and how to prepare them), as well as tasks for the participants.
On the PsychoPy web page, there is a wealth of further resources for teaching and learning to extend what is covered in the two lectures above.
