Understanding Big Data for Public Policy (PPMN90055)
Graduate courseworkPoints: 12.5On Campus (Parkville)
Overview
| Availability | August |
|---|---|
| Fees | Look up fees |
Policy makers need to under what big data is, how it is used, and what ethical and practical issues using big data to make decisions will raise in the 21st Century. They do not need to be programmers. They need to understand, at a high level, the issues involved in using big data for public policy, for the generation of public value.
At the core of this subject is one question: Will decision-making based on standardized measurements from large databases become superior to judgment based upon personal experience and expertise? Decisions based on big data are useful when the experience of any single policy maker is likely to be too limited to develop an intuitive feel for, or reliable measure, of a policy’s efficacy. Statistical analysis can sometimes discover neglected characteristics of a population are more significant than is recognized by intuitive understanding based on accumulated experience. But sometimes, big data—high volume, high velocity, qualitatively various—produces more problems for public policy makers than it solves.
This subject explores all of these important issues, from the basic definitions and history of big data to examples of the use, and misuse, of big data in public policy. No programming knowledge is assumed or required, and none will be taught. The issues for public sector managers raised by this course will be debated and understood using case studies.
Intended learning outcomes
A student who has successfully completed this subject will:
- Understand the history and definition of big data as it applies to public policy
- Recognise the main types of learning models used to derive insights from big data
- Become familiar with the sources of big data in public policy, and
- Grasp the legal and ethical issues involved in using big data for the generation of value for the public.
Generic skills
- A student who has successfully completed this subject will: • Understand the history and definition of big data as it applies to public policy • Recognise the main types of learning models used to derive insights from big data • Become familiar with the sources of big data in public policy, and • Grasp the legal and ethical issues involved in using big data for the generation of value for the public.
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
Please note: to enrol in this subjects students must be enrolled in a masters-level course in the Melbourne School of Government, or its partner Faculties
Corequisites
None
Non-allowed subjects
None
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: 3 November 2022
Assessment
Additional details
- Case study (40%) 1,500-2,000 word precis of a big data problem as applied to a public policy issue, due two weeks after the intensive teaching period.
- Ethical and Bureaucratic issues with big data in public policies (60%), 3,500-4,000 word large review of key literature and cases, due four weeks after the intensive teaching period.
Hurdle requirement: Students are required to attend a minimum of 100% of classes in order to pass this subject and regular class participation is expected
Last updated: 3 November 2022
Dates & times
- August
Principal coordinator Stephen Kinsella Mode of delivery On Campus (Parkville) Contact hours 30 hours Total time commitment 170 hours Pre teaching start date 17 July 2019 Pre teaching requirements Students will be required to access the LMS and the readings provided during the pre-teachingn period. Teaching period 15 August 2019 to 21 August 2019 Last self-enrol date 22 July 2019 Census date 15 August 2019 Last date to withdraw without fail 30 August 2019 Assessment period ends 18 September 2019 August contact information
Time commitment details
Total of 170 hours
Additional delivery details
Please note that this subject is delivered as an intensive and will run from 9:30am until 4:30pm on the scheduled days
Last updated: 3 November 2022
Further information
- Texts
- Links to additional information
- Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
Additional information for this subject
Subject coordinator approval required
- Available to Study Abroad and/or Study Exchange Students
Last updated: 3 November 2022