Unit name | Creating Psychological Experiments |
---|---|
Unit code | PSYCM0056 |
Credit points | 20 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 1 (weeks 1 - 12) |
Unit director | Dr. Quadflieg |
Open unit status | Not open |
Pre-requisites |
n/a |
Co-requisites |
n/a |
School/department | School of Psychological Science |
Faculty | Faculty of Life Sciences |
The unit will introduce a set of core skills for psychologists interested in pursuing a career in research and provide the framework for independent in-depth development of those skills: the ability to design and construct computer based methods for the collection of behavioural data in order to facilitate the assessment of psychological functioning. The unit covers the essentials of using computer-based methods for constructing assessments of psychological functions (e.g., memory) by introducing “PsychoPy”; a python-based open source software for creating and conducting experiments. The aim is to provide a firm foundation so students can build experiments for psychological assessments. This is not intended to be a comprehensive unit in python programming, but a proficiency with the PsychoPy package will be provided so students can construct experiments that involve the essential elements of any assessment (e.g., controlling the screen; creating and presenting shapes, text, animations, movies, and sounds; randomisation; collecting responses; tracking the parameters in operation; and accurately timing events). Only a basic proficiency with computers is assumed, but knowledge of scripting and programming will be an advantage. The unit will provide students with both generic and content specific skills important for the development of computer based psychological assessments.
On completion of the unit, the students will:
Teaching consist of a blend of lectures and practical experience within the software environment given by research active academic staff who use PsychoPy for their research. Before submission of the final working PsychoPy programme, students have two advice clinics to enable them to develop their final submission. Students will showcase their PsychoPy programme where they also receive formative feedback to aid in the improvement of the final submitted PsychoPy scripts and the accompanying methods report.
Design, implement, and describe an experiment using PsychoPy. The assessment includes three interrelated components: a presentation of a working PsychoPy programme (30%) at a “showcase” session, a 1500 word (maximum) report of the experimental design, such as would be found in an APA research paper describing the experiment (35%) and the PsychoPy script used for running the experiment (35%).
Peirce, J. W. (2007). PsychoPy – Psychophysics software in Python. Journal of Neuroscience Methods, 162, 8-13.
Peirce, J. W. (2009). Generating stimuli for neuroscience using PsychoPy. Frontiers in Neuroinformatics, 2, 10.