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PYMPBC1-Programming for Behavioural and Cognitive Neurosciences
Module Provider: Psychology
Number of credits: 20 [10 ECTS credits]
Level:7
Terms in which taught: Spring term module
Pre-requisites:
Non-modular pre-requisites: Graduate level quantitative skills relevant to Psychology and familiarity with computers
Co-requisites:
Modules excluded:
Current from: 2020/1
Email: p.scarfe@reading.ac.uk
Type of module:
Summary module description:
Being able to program experiments and understand experimental design in an essential component of doing scientific research in Behavioural and Cognitive Neuroscience.Ìý This course will introduce you to programming and experimental design in Matlab. The primary focus will be on Matlab is this is one of the most widely used programming languages in Psychology and Cognitive Neuroscience.
Aims:
The module will introduce students to basic programming skills necessary to design psychology experiments and analyze data through a set of seminars and hands-on practical sessions.
Assessable learning outcomes:
By the end of the course students will:
- Be able to efficiently use and navigate the Matlab and E-Prime programing environments.
- Have a clear understanding of the tasks, measures and methods used for research in Behavioural and Cognitive Neuroscience
- Have good working knowledge of how to construct experiments in E-Prime and Matlab
- Have a good working knowledge of how to analyse experimental data in Matlab.
Additional outcomes:
It is anticipated that this module will inform much subsequent work by students on postgraduate courses in psychology and related disciplines. Programming skills are highly transferable, and hence will benefit students in any future profession that involves using a quantitative/ analytic approach.
Outline content:
The course will consist of nine three-hour sessions.
Session 1: Introduction to Experimental Design and Programming
Session 2: Introduction to programming in MatlabÌý#1
Session 3: Introduction to programming with Matlab #2
Session 4:ÌýProgramming Experiments with Matlab and Psychtoolbox #1
Session 5: Pr ogramming Experiments with Matlab and Psychtoolbox #2
Session 6: Programming Experiments with Matlab and Psychtoolbox #3
Session 7: Analysing data with Matlab and Palamedes #1
Session 8: Analysing data with Matlab and Palamedes #2
Session 9: Exam
Brief description of teaching and learning methods:
This module will be taught through a mix of plenary lectures to introduce specific topics, and accompanying practical work to provide hands-on training.
Ìý | Autumn | Spring | Summer |
Practicals classes and workshops | 24 | ||
Guided independent study: | 176 | ||
Ìý | Ìý | Ìý | Ìý |
Total hours by term | 200 | ||
Ìý | Ìý | Ìý | Ìý |
Total hours for module | 200 |
Method | Percentage |
Practical skills assessment | 100 |
Summative assessment- Examinations:
The exam will take place in the final session of the course.Ìý
Summative assessment- Coursework and in-class tests:
Formative assessment methods:
Assessment will be 70% continuous (7 homework’s each worth 10%) and 30% final exam. Homework will be set at the end of Sessions 2-8 and will be handed in at the beginning of the next session
Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx
Assessment requirements for a pass:
50%
Reassessment arrangements:
Additional Costs (specified where applicable):
None
Last updated: 4 April 2020
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.