PY2SCP: Scientific Computing for Psychologists

Module code: PY2SCP

Module provider: Psychology; School of Psych and Clin Lang Sci

Credits: 20

Level: Level 2 (Intermediate)

When you'll be taught: Semester 2

Module convenor: Dr Peter Scarfe, email: p.scarfe@reading.ac.uk

Pre-requisite module(s): BEFORE TAKING THIS MODULE YOU MUST TAKE PY1INM (Compulsory)

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: No

Talis reading list: No

Last updated: 23 May 2024

Overview

Module aims and purpose

Students will be introduced to the basics of scientific computation for data analysis and visualisation, building on the neuroscience methods introduced in the prerequisite module PY1INM. Consequently, examples and problems will be drawn mostly from neuroscience, psychology, psychophysics and neuroimaging. The foundational skill taught is programming (coding, scripting) in Python and will make use of appropriate widely used scientific libraries and packages e.g., PsychoPy for running behavioural experiments in Python. All work will be carried out in the computer lab, with a strong focus on solving problems to acquire practical skills, and assessment is based primarily on completing two computational projects. 

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. Code in Python at a basic to intermediate level 
2. Know how to use scientific libraries and packages in data analysis workflowsin Python 
3. Be competent at coding typical data visualisation tasks in Python 
4. Understand and be able to program core elements of behavioural experiments in Python and the PsychoPy package. 

Module content

The module includes topics such as the following: 

• Software: introduction to Python and their associated libraries / ecosysteme.g., PsychoPy. 
• Lab / project work: programming as creative problem solving and data handling. 
• Programming: data types, data structures, control structures, logic, and libraries. 
• Data analysis: arrays, data frames, indexing, mathematical operations on data structures. 
• Data visualisation: line plots, subplots, log & polar plots, scatter & 3D plots, image manipulation and processing. 
• Design and coding of core elements of Psychology experiments (using PsychoPy) e.g., stimulus presentation, response collection, data saving, looping over trials in an experiment. 

Structure

Teaching and learning methods

The module is split into two sections, each five weeks long. Each block culminates in the setting of a computational project (worked on individually and independently). The skills needed to complete this project are acquired throughout the corresponding section of the course.The project set in section two of the course will require knowledge from both section one and two, demonstrating students active engagement with the full materials of the course.  

Contact hours consist of sessions consisting of lectured material and computer labs combined fluidly. The focus will be on students actively learning through guided programming tasks (engaged experimentation is key).  

A typical two-hour session consists of an initial presentation, followed by exercises students work on, assisted and guided by the teaching team. Formative feedback is given throughout each session at any point and in a student-led manner so as to constructively align to each students learning needs. Students are encouraged to actively engage with the feedback available to them throughout the course.  

Projects are designed to utilise and extend skills acquired in the course. The dedicated project briefing weeks are an opportunity for students to (1) be briefed on the project, and (2) actively engage in opportunities for learning available to them. 

Study hours

At least 36 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Formative assessment is available throughout the course by students actively engaging in the materials taught to them. This can be in the form of question in class, or organised one-to-one meetings with teaching staff. It is student-led and constructively aligned to the students’ learning needs.  

Reassessment

Additional costs