PY3CMC-Computational Models and Methods in Psychology

Module Provider: Psychology
Number of credits: 10 [5 ECTS credits]
Level:6
Terms in which taught: Autumn term module
Pre-requisites: PY2RM Research Methods and Data Analysis or PY2RMP Research methods in Psychology
Non-modular pre-requisites:
Co-requisites:
Modules excluded:
Current from: 2022/3

Module Convenor: Prof Ingo Bojak
Email: i.bojak@reading.ac.uk

Type of module:

Summary module description:

This module provides students with the opportunity to learn about the application of mathematical and computational models to the study of cognition and behaviour. It also introduces aspects of advanced data analysis and covers some practical matters relevant to modelling, in particular parameter fitting and model comparison. The general role of modelling in psychological research will be discussed and different types of models will be distinguished. A number of computational models that have been used in psychology will be introduced, and various issues in the implementation and interpretation of their results will be considered.ÌýÌý

This module is delivered at the ºÚ¹Ï³ÔÁÏÍø only.ÌýÌý

Aims:

This module aims to provide a basic understanding of the place of modelling in science in general, and psychology in particular. To this end, both the philosophy behind the introduction of a model and the practicalities of implementing it in a fruitful manner will be considered. The module also aims to introduce scientific software and their usage in modelling, through hands-on computer labs. Finally, the module aims to familiarise students with some of the modelling strategies and individual models currently popular in psychology.

Assessable learning outcomes:

By the end of the module, students will be able to:

1. Discuss and critically appraise the impact of computational modelling in science and of particular computational models in psychology.


2. Manipulate computational models and analyse data in scientific software packages (in particular R/RStudio).


3. Evaluate the modelling and analysis results in order to arrive at quantitative and qualitative conclusions.

Additional outcomes:

In addition, students will be able to:

• Interpret mathematical notation commonly used in specifying models.


• Gain some insight into how computational models are programmed in practice.

Skills that will be developed include

• Computer literacy with regards to using scientific software (in particular R/RStudio).


• Data-handling & analysis, as well as numeracy, through the application of computational modelling and methods.


• Problem solving and teamwork, through practical exercises and group work in the computer labs.

Outline content:

This module comprises seven two-hour seminars.Ìý Each seminar will consist of a lecture on a specific topic, followed by an interactive computer lab in which students explore the topic using scientific software packages (in particular R/RStudio). In the computer lab students will learn to employ and modify existing programs and tools. Topics might include modelling as a scientific method, two-choice reaction time tasks, model fitting, connectionist models, reinforcement learning, model comparison and Bayesian methods.Ìý

Brief description of teaching and learning methods:

The module will use a combination of lectures and interactive computer labs, as well as individual reading and computer work. The lectures will provide an initial overview on a topic, whereas the computer labs provide space for practical exploration, group work and interactive discussion. Directed reading will help students to appreciate the wider context and contemporary research trends. It is expected that students will work individually with the employed software and computational models o utside the computer labs. In order to prepare students for the coursework assessment, students will have the opportunity to practice their report writing skills relevant to the lab classes and receive formative feedback.Ìý

Contact hours:

Ìý	Autumn	Spring	Summer
Seminars	14
Guided independent study:	Ìý	Ìý	Ìý
Ìý Ìý Wider reading (directed)	16
Ìý Ìý Preparation for tutorials	14
Ìý Ìý Preparation of practical report	28
Ìý Ìý Completion of formative assessment tasks	14
Ìý Ìý Essay preparation	14
Ìý	Ìý	Ìý	Ìý
Total hours by term	100	0	0
Ìý	Ìý	Ìý	Ìý
Total hours for module	100

Summative Assessment Methods:

Method	Percentage
Report	100

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

This module is assessed through coursework, namely through the submission of one written report at the beginning of Spring term (100%). The report will consist of two parts. The first part will require concise answers of the student to a series of questions of mathematical, computational, and conceptual nature. These questions will be set by the convenor. The second part will consist of a short technical essay (1,250 words) reporting on a computational model and its application in psychology. While the detailed requirements and general topic / domain will be set by the convenor, students otherwise will choose freely what work to research and report on.

Formative assessment methods:

Students will receive feedback opportunities linked to all their laboratory activity, which will directly support their coursework. Furthermore, around mid-term students will be provided with a mock coursework of the same structure as the summative assessment, but about half its length. They will receive general feedback on solutions, and if they submit their own attempt can obtain individual feedback as well.

Penalties for late submission:

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

• 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 five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

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

Assessment requirements for a pass:

A mark of at least 40% overall

Reassessment arrangements:

Resit assessment/examination in the August resit period.

Additional Costs (specified where applicable):

1) Required text books:Ìý

2) Specialist equipment or materials:Ìý

3) Specialist clothing, footwear or headgear:Ìý

4) Printing and binding:Ìý

5) Computers and devices with a particular specification:Ìý

6) Travel, accommodation and subsistence:Ìý

Last updated: 22 September 2022