Unit convenor and teaching staff |
Unit convenor and teaching staff
Erik Reichle
Donna Keeley
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Credit points |
Credit points
3
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Prerequisites |
Prerequisites
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Corequisites |
Corequisites
PSY490 or PSY495
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Co-badged status |
Co-badged status
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Unit description |
Unit description
This unit will provide an introduction to computational modeling in (cognitive) psychology. The main goals of this unit are to foster both a basic understanding of the different approaches to modeling and an appreciation of the practical and philosophical issues related to modeling. The first part of the unit will focus on the following questions: (1) What are computational models of cognition?; (2) What are the major approaches (e.g., production systems) that are used to model cognitive processes?; (3) How are models developed and used in research?; and (4) How are models compared and evaluated? The second part of the unit will examine these issues in more depth by comparing models that have been developed to account for phenomena in specific areas of cognitive research (e.g., episodic memory). The final part of the unit will consist of student-led discussions of seminal modeling papers from the students’ areas of interest. Students will also complete a modeling project or write a critique/review of existing models within their area of interest.
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Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
On successful completion of this unit, you will be able to:
Name | Weighting | Hurdle | Due |
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Essay #1: Describe a model | 25% | Yes | 23/8/19 |
Essay #2: Compare 3 approaches | 25% | No | 4/10/19 |
Essay #3: Compare 3 models | 50% | No | 15/11/19 |
Due: 23/8/19
Weighting: 25%
This is a hurdle assessment task (see assessment policy for more information on hurdle assessment tasks)
Students will be required to write a brief (500-word) essay describing a computational model (MINERVA 2; Hintzman, 1986) using only words (i.e., not equations). This assessment will demonstrate the capacity to read and understand formal (e.g., mathematical) descriptions of computer models, as well as describe that model in a more informal manner to someone else.
Due: 4/10/19
Weighting: 25%
Students will be required to write a brief (500-word) essay summarizing the main differences between three alternative approaches to modeling: mathematical/statistical models, production systems, and artificial neural networks. The assessment will demonstrate knowledge of the different approaches to modeling, as well as their strengths and weaknesses.
Due: 15/11/19
Weighting: 50%
Students will be required to compare and contrast 3 models of a particular research domain (e.g., human concept learning). This assessment will demonstrate a high-level capacity to understand descriptions of formal models and the phenomena that they are intended to explain, and to then integrate that knowledge as required to critically evaluate the relative merits of the models in their capacity to explain a set of empirical findings.
All required articles are provide on iLearn.
Macquarie University policies and procedures are accessible from Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central). Students should be aware of the following policies in particular with regard to Learning and Teaching:
Undergraduate students seeking more policy resources can visit the Student Policy Gateway (https://students.mq.edu.au/support/study/student-policy-gateway). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
If you would like to see all the policies relevant to Learning and Teaching visit Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central).
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/study/getting-started/student-conduct
Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
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When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.
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