Module Code:

PS901

Module Name:

Computational Modelling

Module Credits (CATS):

15 CATS / 10 CATS (DTP version)

Module Convener

James Adelman

Module Teachers

James Adelman

Module Aims

To introduce students to the practice of computational modelling in Psychology.

Learning Outcomes

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

• Critically evaluate claims regarding the purpose and conduct of computational modelling in Psychology.
• Simulate (some) models in Psychology.
• Conduct statistical analyses of the performance of models in Psychology (with reference to data).
• Report computational modelling in a Psychological research paper context.

Assessed by:

worksheets

final report

Module Work Load

Module Length

10 weeks

Lectures

Seminars

20 hours workshops

Attendance

Module Assessment

Regular worksheets

10%

final report

90%

Module Programme

Purpose of computational modelling; tools for computational modelling; describing computational models; assessing and comparing computational models; reporting results of computational modelling; detailed specific examples of computational models, drawn (on a non-fixed basis) from language, memory, perception, attention, categorization etc., to illustrate critical points in the above.

Module Reading List

General background from (i.e., the MATLAB examples will not be used):

Lewandowsky, S., & Farrell, S. (2011). Computational modeling in cognition: Principles and practice. Thousand Oaks, CA: Sage.

At a more specific level, we will rely on:

Papers, on a rotating basis, to reflect the current year’s specific example topics and models.