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PSY-40103 - Module Specification
School of Psychology
Faculty of Natural Sciences

For academic year: 2023/24 Last Updated: 13 February 2024

PSY-40103 - Advanced Computational and Statistical Approaches to Behaviour
Coordinator: Chris Street Tel: +44 1782 7 33386
Lecture Time: See Timetable...
Level: Level 7
Credits: 15
Study Hours: 150
School Office: 01782 733736

Programme/Approved Electives for 2023/24

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2023/24

Understanding behaviour is challenging because of the complexity of the mind, a wide range of situational and social influences on it, and individual differences amongst people. Researchers tackle this complexity using a variety of computational and statistical approaches. This module will provide you with a grounding in a selection of advanced quantitative methods, leaving you with a rich and integrated understanding of how computational and statistical methods can be used to predict behaviour and test scientific theories. Indicative topics include machine learning, cognitive modelling, Bayesian analysis, and agent-based modelling.

Aims
This module will introduce students to various advanced computational and statistical approaches to understanding behaviour. The module will provide students with a solid understanding of these approaches, and students will critically engage with how these approaches have been utilised to address a research question of interest to the student.

Intended Learning Outcomes

Handle and prepare research data for use with advanced computational and statistical approaches to understanding behaviour
: 1,2
Deploy a variety of advanced computational and statistical approaches to understanding behaviour: 1,2
Interpret the results of advanced computational and statistical approaches to understanding behaviour: 1,2
Critically evaluate competing cognitive theoretical perspectives using advanced computational techniques: 2
Communicate a research project for a scientific audience: 2

Study hours

- 24 hours of scheduled synchronous teaching (interactive, discussion-based etc.)
- 24 hours of preparation for upcoming teaching sessions
- 12 hours of guided asynchronous learning
- 90 hours preparing for and completing the multiple choice assessment

School Rules

None

Description of Module Assessment

1: Multiple Choice Questions - Knowledge weighted 30%
Analytical Practical
Students will be assigned data sets relevant to the techniques that they have learnt on the module and be required to implement the computational and statistical approaches learnt on the module in order to answer a set of multiple choice questions. Addressing the questions will require understanding the nature of the data, and having competence in carrying out and interpreting the results of the methods that they have learnt. Twenty questions will be set as part of the assessment. The questions will be related to the techniques taught between Weeks 1 and 6. The questions will be released to students two weeks before the end of the assessment period.

2: Laboratory Report weighted 70%
3000 word cognitive modelling lab report
Students will be assigned a data set and be required to programme a computational cognitive model to compare two cognitive theoretical accounts of human thinking or behaviour. The results will be reported in a 3,000 word lab report, which will include an abstract, introduction, methods, results, discussion and references section. Students will be required to upload their code alongside their assessment, but the code will not be formally graded. Rather, it will be used when necessary to obtain clarification of what is reported.

Please note that for the 2022/23 Academic Year programmes may be adapted to operate in accordance with a flexible, digital approach. This means that there may be some changes made to how modules are delivered and assessed. The latest information will be provided to you by your School in module handbooks. We endeavour to give you as much notice as possible of any changes and details about the circumstance in which changes are made to programmes can be found in the Student Agreement, available at: https://www.keele.ac.uk/student-terms-and-conditions/

Last Updated: 13 February 2024