Please note: there may be some adjustments to the teaching arrangements published in the course catalogue for 2020-21. Given current circumstances related to the Covid-19 pandemic it is anticipated that some usual arrangements for teaching on campus will be modified to ensure the safety and wellbeing of students and staff on campus; further adjustments may also be necessary, or beneficial, during the course of the academic year as national requirements relating to management of the pandemic are revised.

Big Data, Policy & Power PUBPOL4044

  • Academic Session: 2021-22
  • School: School of Social and Political Sciences
  • Credits: 20
  • Level: Level 4 (SCQF level 10)
  • Typically Offered: Semester 2
  • Available to Visiting Students: Yes
  • Available to Erasmus Students: Yes

Short Description

This course offers an opportunity for students to critically examine the role and use of big data in policy and society. Students will focus on exploring a range of perspectives and applications of big data and gain an understanding of how big data analytics are being employed and developed in the public, private, and voluntary sectors/civil society and in different cultural contexts.

Students will also have the chance to unpack and evaluate big data as a methodological approach, which is increasingly applied in various policy domains and for different purposes. This course will provide students the space to critically reflect on the potential risks and opportunities associated with the increased use of big data in the digital age and discuss what it means for policy and practice now and in the future.

Timetable

One hour weekly lecture

One hour weekly seminar

Requirements of Entry

Entry to Honours Social & Public Policy normally requires a grade point average of 12 (grade C3) over Social & Public Policy 2A and 2B (formerly Public Policy 2A and 2B) as a first attempt.

Excluded Courses

None

Co-requisites

None

Assessment

One written assignment (3000 words), weighted at 60%. Students will be assessed based on two blog posts (1500 words each) that relate to at least one topic covered in the course.

One reflective summary (300 words), weighted at 15%. Students will be asked to reflect on writing for public/policy audience and how they used literature and research to develop the writing of the blog posts/written assignment.

One report (1000 words), weighted at 25%. Students will be asked to develop a policy briefing in the style of a "fact sheet" that is aimed towards condensing information to inform policy and change practice of a public sector, third sector, or industry organisation of their choice.

Are reassessment opportunities available for all summative assessments? Not applicable for Honours courses

Reassessments are normally available for all courses, except those which contribute to the Honours classification. Where, exceptionally, reassessment on Honours courses is required to satisfy professional/accreditation requirements, only the overall course grade achieved at the first attempt will contribute to the Honours classification. For non-Honours courses, students are offered reassessment in all or any of the components of assessment if the satisfactory (threshold) grade for the overall course is not achieved at the first attempt. This is normally grade D3 for undergraduate students and grade C3 for postgraduate students. Exceptionally it may not be possible to offer reassessment of some coursework items, in which case the mark achieved at the first attempt will be counted towards the final course grade. Any such exceptions for this course are described below. 

Course Aims

The aims of the course are to:

■ Develop understandings of what big data is and how it is being used as a method and a tool in a range of domains, such as national and local government, health, businesses and finance, education and research, citizen participation, social networks, community activism, policing, city/urban developments, and other social and technological innovations related to policy and practice.

■ Examine a range of contentious and cutting-edge issues regarding the benefits and challenges of applying big data analytics and associated forms of technology (e.g. algorithms, artificial intelligence, smart devices, Internet of Things, and mediatised platforms), and consider how their developments may influence policy and society in different ways.

■ Explore questions about the role of big data in policy and practice, such as how big data can be used, how it may be mis-used, what it is used for, and by whom.

■ Discuss various issues associated with power (who owns and has control), regulations, and practices of collecting and exploiting big data that may reinforce inequalities and exclusions or create new ones in society. On other hand, to consider various approaches and opportunities to the use of big data that may promote innovation, improve society and well-being, and/or empower citizens and community actions in new ways in different parts of the world.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

■ Identify what big data is and means for policy and society in the 21st century and explore the practices of how big data is used in a range of sectors (such as government, policy, education and research, community and civil society, and private industry).

■ Reflect on the role of big data analytics and how and why it is being developed and applied as a methodological and analytical tool in different ways to achieve social, economic, cultural, political and/or policy goals.

■ Critically evaluate the opportunities and risks presented by the increased use of big data and analyse what potential benefits and challenges its application in policy and society may present now and in the future.

■ Evaluate a range of policy and societal issues associated with the applications and approaches of big data in different countries and cultural contexts and discuss potential policy, community, and individual responses to social and technological innovations related to changing policy and practices in the digital age.

Explore and utilise research, evidence, and conceptual and theoretical resources from a range of disciplines related to studies of big data to facilitate independent learning, critical thinking, and communication with a range of audience.  

Minimum Requirement for Award of Credits

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.