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This is an illustration of how to run a jsPsych experiment from pavlovia.org, using the jsPsych pavlovia plugin.

This experiment demonstrates a method to randomize a fixation cross duration. This specific method shows the randomization between 1000ms and 3000ms.

Working memory tests on JavaScript (digit span, operation span, visual array, spatial span)

Sustained Attention to Response Time Task (SART)

A simple lexical decision task to check stimuli.

The Choice Reaction Time Task (Deary & Liewald, 2011)

Ejemplo

Eksperimen ini bertujuan untuk mengklasifikasikan gambar-gambar wajah sesuai dengan emosi dasar manusia (terkejut, takut, jijik, marah, senang dan sedih).

Eksperimen terdiri dari dua bagian. Bagian PERTAMA, Anda diminta untuk menentukan emosi yang cocok/sesuai dengan gambar yang diberikan serta menentukan intensitas emosi pada gambar yang diberikan. Bagian KEDUA, Anda diminta untuk memilih satu kata emosi yang paling cocok/sesuai dengan gambar dari dua pilihan kata yang diberikan.

Eksperimen ini merupakan rangkaian dari validasi Human Basic Expressions Test yang dapat digunakan untuk seting klinis seperti pengukuran kemampuan pengenalan ekspresi wajah pada individu dengan Autism Spectrum Disorder.

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This task shows you the drag and drop capabilities of PsychoPy and PsychoJS. The demonstration uses a drag and drop puzzle game. The task requires you to drag and drop the black and white pieces into the empty square.

Transcription demo using Microsoft Cognitive Services

a la Woods et al

This is a simple Lexical decision task. A fixation cross will be displayed in the centre of the screen. Following this 2 text stimuli will then appear, and the participant will have to respond if they are words or non words pressing ‘w’ if they are both words or ‘n’ if one or more is not a real word. This will be repeated 36 times for the main trial. Reaction time and accuracy will be recorded, and congruent and incongruent pairs will be compared. If you have any issues please get in touch with me at 19010167@hope.ac.uk Thank you Michael Dolan 19010167@hope.ac.uk