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Introduction to Experience Sampling (PSYC90109)
Graduate courseworkPoints: 12.5Online
About this subject
- Overview
- Eligibility and requirements
- Assessment
- Dates and times
- Further information
- Timetable(opens in new window)
Contact information
Term 2
Prof Simon Dennis
Melbourne School of Professional and Continuing Education
Further information: https://study.unimelb.edu.au/find/courses/graduate/master-of-applied-analytics
Email: continuing-education@unimelb.edu.au
Phone: + 61 3 8344 0149
Monday to Friday 8am to 9pm AEST/AEDT. Weekends and University of Melbourne observed Public Holidays 10am to 5pm AEST/AEDT.
Overview
Availability | Term 2 - Online |
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Fees | Look up fees |
Dense data sources such as smartphones, social networks, wearable sensors and the internet of things are being used to provide an unparalleled window into psychological processes as they occur in the real world. In this subject, we will train you in the collection and analysis methods that are applicable to experience sampling data from dense data sources. As the data is often sensitive, we will also explore the security and privacy issues that need to be considered when conducting experience sampling studies.
- Completion of this subject requires each individual student to collect and analyse experience sampling data about themselves - it is not possible to opt out of this activity. This experience sampling data will be confidential to the individual student and will not be visible to others.
Intended learning outcomes
To provide psychological professionals and researchers in the community, defence, health and government sectors the capability to:
- Collect data from both active and passive experience sampling sources such as smartphones, social media, wearable devices and the internet of things;
- Appreciate the ethical considerations and methods for mitigating security and privacy issues specific to experience sampling data;
- Use a variety of analysis methods including Bayesian models, machine learning and dynamic systems techniques appropriate to experience sampling data;
- Develop skills in the presentation of experience sampling data
Generic skills
- High level written communication skills;
- Advanced information and interpretation skills;
- Advanced analytic, integration and problem-solving skills;
- Competence in critical and theoretical thinking through essay writing and online discussions.
Last updated: 3 November 2022