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Models of Psychological Processes (PSYC40012)
HonoursPoints: 12.5On Campus (Parkville)
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable (login required)(opens in new window)
Contact information
Semester 2
Prof Philip Smith
Overview
Availability | Semester 2 |
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Fees | Look up fees |
This subject is designed to introduce students to the development and testing of models for psychological data, with a focus on models of human cognition. Quantitative data is a feature of all areas of psychology and can only be interpreted by use of an appropriate model. Modelling in psychology has two aims. The first is to find a quantitative description that accurately captures the data. The second is to test competing hypotheses about the psychological processes that generated the data. The methods of psychological modelling will be introduced and illustrated in selected areas of cognitive psychology.
The subject comprises a series of nine two-hour seminars covering the conceptual, theoretical, and methodological issues involved in developing and evaluating quantitative models of human cognitive performance. The seminars are complemented by nine two-hour laboratory classes in which students will learn how to use the modelling language Matlab to fit, visualise, and evaluate models of data from specific cognitive domains, such as attention, categorisation, and decision making.
Intended learning outcomes
Knowledge
On completion of this subject, students should demonstrate an understanding of:
- The concepts and methods involved in the development, testing, and evaluation of quantitative models for psychological data.
- The philosophical and methodological distinction between hypothesis-testing and model evaluation.
- The trade-off between goodness-of-fit and model flexibility and its implications for psychological inference.
- The distinction between process models and empirical models of psychological data.
Skills
On completion of this subject, students should be able to:
- Use quantitative modelling software to fit models to selected data sets from the cognitive literature.
- Use model-selection methods to compare the performance of alternative models and interpret the results.
- Communicate the results of a model-based evaluation of cognitive performance effectively in written form.
- Make use of both graphical and quantitative measures of fit to reason effectively about the psychological processes underlying particular patterns of experimental data.
Application of Knowledge and Skills
On completion of this subject, students should be able to:
- Evaluate and critically assess model-based studies in the published research literature
- Apply model-based methods to their own independent research
- Bring a model-based perspective to the critical analysis of published research that uses traditional hypothesis-testing methods.
Generic skills
This subject aims to:
- Develop critical and analytical thinking about quantitatively expressed theories and models.
- Develop skills in drawing inferences about the relationship between unobserved structures and processes and their observed manifestations or expressions.
- Provide experience in quantitative, evidence-based evaluation of scientific theories.
- Develop expertise in the use of modelling software for quantitative psychological data.
Last updated: 31 January 2024
Eligibility and requirements
Prerequisites
There are no pre-requisites for this subject.
Corequisites
None
Non-allowed subjects
There are no non-allowed subjects.
Recommended background knowledge
An accredited psychology major sequence.
Inherent requirements (core participation requirements)
The University of Melbourne is committed to providing students with reasonable adjustments to assessment and participation under the Disability Standards for Education (2005), and the Assessment and Results Policy (MPF1326). Students are expected to meet the core participation requirements for their course. These can be viewed under Entry and Participation Requirements for the course outlines in the Handbook.
Further details on how to seek academic adjustments can be found on the Student Equity and Disability Support website: http://services.unimelb.edu.au/student-equity/home
Last updated: 31 January 2024
Assessment
Description | Timing | Percentage |
---|---|---|
Take-home exam
| Mid semester | 40% |
Essay
| End of semester | 60% |
Last updated: 31 January 2024
Dates & times
- Semester 2
Mode of delivery On Campus (Parkville) Contact hours 36 hours per semester Total time commitment 170 hours Teaching period 22 July 2024 to 20 October 2024 Last self-enrol date 2 August 2024 Census date 2 September 2024 Last date to withdraw without fail 20 September 2024 Assessment period ends 15 November 2024 Semester 2 contact information
Prof Philip Smith
Time commitment details
Estimated total time commitment 170 hours per semester.
What do these dates mean
Visit this webpage to find out about these key dates, including how they impact on:
- Your tuition fees, academic transcript and statements.
- And for Commonwealth Supported students, your:
- Student Learning Entitlement. This applies to all students enrolled in a Commonwealth Supported Place (CSP).
Subjects withdrawn after the census date (including up to the ‘last day to withdraw without fail’) count toward the Student Learning Entitlement.
Last updated: 31 January 2024
Further information
- Texts
Prescribed texts
A reading pack and lecture notes will be provided.
Recommended texts and other resources
No recommended texts.
- Related Handbook entries
This subject contributes to the following:
Type Name Course Graduate Diploma in Psychology (Advanced) Informal specialisation Psychology
Last updated: 31 January 2024