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HS52008: Digital methods and data skills for MRes

[Page last updated: 15 August 2024]

Academic Year: 2024/25
Owning Department/School: Faculty of Humanities & Social Sciences (units for MRes programmes)
Credits: 5 [equivalent to 10 CATS credits]
Notional Study Hours: 100
Level: Masters UG & PG (FHEQ level 7)
Period:
Semester 1
Assessment Summary: CWRI 100%
Assessment Detail:
  • Research proposal (CWRI 100%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites:
Learning Outcomes: By the end of the course students are expected to: - develop an understanding of the current digital environment and its social implications - understand the systemic effects that recent digital developments and new forms of data have had on academic research - become competent consumers of digital and computational research (academic and non-academic) - understand the functioning, range of application, assumptions and limitations of a range of qualitative, quantitative and computational methods for digital data collection and analysis - appreciate the rationale for using different types of methods contingent upon a studyâs research objectives - develop the ability to make methodological and research design choices involving the use of digital data and methods - become competent and confident data managers - understand the ethical and legal issues surrounding digital data collection and analysis


Synopsis: Develop your ability to understand, collect and analyse complex and evolving forms of digital data. You'll receive:
  • a foundational overview of the variety of digital data sources used for research across multiple social science disciplines
  • an introduction to range of computational, quantitative and qualitative methods that can be used to collect and analyse specific forms of digital data.
Throughout this unit, you'll also learn about ethical and research quality issues.

Content:
  • The digital revolution and its social and epistemological implications.
  • Forms of digital data and the ways in which they are used across social science disciplines.
  • Methods and tools of digital and ¿big¿ data collection ¿ providing an overview of computational and non-computational options.
  • Data storage and management ¿ including secure data storage, GDPR, open science principles and reproducible research standards and practices.
  • Introduction to a range of digital (qualitative and quantitative) methods for text, network and image analysis.
  • Conceptual understanding of machine learning and recent AI applications, with examples from multiple disciplines.
  • Presenting and interpreting the outputs of digital analysis.
  • Quality assurance, robustness checks, validity and reliability, and bias avoidance in the context of digital research.
  • Ethical and legal issues surrounding digital data collection and analysis.


Course availability:

HS52008 is a Must Pass Unit on the following courses:

Department of Politics, Languages and International Studies

HS52008 is Compulsory on the following courses:

Department of Education Department for Health Department of Politics, Languages and International Studies Department of Psychology Department of Social & Policy Sciences

Notes:

  • This unit catalogue is applicable for the 2024/25 academic year only. Students continuing their studies into 2025/26 and beyond should not assume that this unit will be available in future years in the format displayed here for 2024/25.
  • Courses and units are subject to change in accordance with normal University procedures.
  • Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.
  • Find out more about these and other important University terms and conditions here.