PY2SCP: Scientific Computing for Psychologists

Module code: PY2SCP

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

Credits: 20

Level: 5

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: 2025/6

Available to visiting students: No

Talis reading list: No

Last updated: 3 April 2025

Overview

Module aims and purpose

Students will be introduced to the basics of scientific computation in Python for data analysis visualisation and programming of behavioural experiments. This will build upon and extend the neuroscience methods introduced in the prerequisite module PY1INM. Examples and problems will be drawn from a diverse range of areas 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. All work will be carried out in the computer lab, with a strong focus on solving problems to acquire practical skills.

Module learning outcomes

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

1. Program in Python at a basic to intermediate level
2. Know how to use scientific libraries and packages in data analysis workflows in 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 PsychoPy

Module content

The module includes topics such as the following:

• Software: introduction to Python and their associated libraries / ecosystem e.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

The module incorporates BPS core content in the following areas: biological psychology and research methods.

Structure

Teaching and learning methods

The course is designed to allow students to hone and practice their skills, which is an essential skill whilst learning programming, prior to being summative assessed. The module is split into two sections, each culminating in an in-class test. The first assesses material form the first part of the course, the second from both the first and second parts of the course with a weighting towards the latter.

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 and through attending the teaching teams weekly student drop-in hours.

Study hours

At least 30 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.

Students will receive formative feedback throughout the course during the weekly labs / practicals. Students can gain further formative feedback through online discussion boards and the student drop-in hours of the teaching team.

Reassessment

Additional costs