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  3. Introduction to Experience Sampling

Introduction to Experience Sampling (PSYC90109)

Graduate courseworkPoints: 12.5Online

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Overview

Year of offer2019
Subject levelGraduate coursework
Subject codePSYC90109
Availability
Term 2 - Online
FeesSubject EFTSL, Level, Discipline & Census Date

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 April 2019