Course Structure

The programme is designed to provide a fundamental grounding in both quantitative and qualitative research skills, along with the opportunity to specialise in new methods and in practical applications of research techniques.

The MRes is awarded to students who successfully complete taught modules amounting to 120 CATS and a research dissertation (60 CATS points).

The programme can be completed in one year on a full-time basis or over two or three years part-time.

The modules are delivered via a mixture of traditional lecture, seminar, workshop and computer lab class. Students are expected to undertake a substantial amount of independent study at this level. Master’s students completing a dissertation will meet one-to-one with their academic supervisor throughout the course of their studies to provide guidance on their project.

Course Details

The programme is designed to provide a fundamental grounding in both quantitative and qualitative research skills, along with the opportunity to specialise in more advanced training in quantitative research, qualitative research or in practical applications of research techniques. CORE MODULES: Semester 1 Research Design (20 CATS) This module offers an introduction to the different styles of social science research as well as guidance and illustrations of how to operationalize research questions and assess them empirically. Students will be shown how to conduct systematic literature searches and how to manage ethical issues with different empirical research projects. The module will also explore the connection between social science research and policy concerns. It is designed as preparation for undertaking postgraduate research and dissertation work. Theory and Debates in Social Research (20 CATS) This module aims to deepen students' understanding of key debates in social theory and research, providing advanced level teaching for those building upon basic knowledge and undertaking postgraduate research. It is designed to demonstrate and explore how social theory is utilised, critiqued and developed through the pursuit of social science research. The Sources and Construction of Qualitative Data (10 CATS) The purpose of this module is to illuminate the theoretical underpinnings of qualitative research. The module will discuss the impact of various theories on the nature and conduct of qualitative research particularly around questions of epistemology and ontology. It will discuss methods of data collection such as individual and collective interviewing in qualitative research, and explore the issues connected with the relationship between theory and methods. The Sources and Construction of Quantitative Data (10 CATS) The aim of the module is to provide a comprehensive overview of the theory and practice of measurement and constructing quantitative data in the social sciences. Through lectures and practical exercises, this module will provide students with relevant knowledge of secondary data sources and large datasets, their respective uses and usefulness, and their relevance for the study of contemporary social issues Semester 2 Qualitative Data Analysis (10 CATS) The module will provide students with an overview of different approaches to qualitative data analysis. It will include introductory training to this skill that includes such techniques as thematic analysis and discourse analysis, as well as computer assisted qualitative data analysis. It will provide the knowledge necessary for the informed use of the qualitative data analysis software package NVivo. The module gives students a base level introduction to the analytical and technical skills in qualitative data analysis appropriate to the production of a Master's dissertation and/or use of CAQDAS software for social science research purposes. Quantitative Data Analysis: Foundational (10 CATS) This module provides an introduction to the basics of quantitative data analysis. The module will begin with a brief review of basic univariate and bivariate statistical procedures as well as cover data manipulation techniques. The module is taught through a series of seminars and practical workshops. These two strands are interwoven within each teaching session. Please note that students may be granted an exemption from this module if they have already successfully completed a module that has the equivalent learning outcomes. Quantitative Data Analysis: Intermediate (10 CATS) This module advances students' confidence and knowledge in the use of SPSS. The module focuses on multivariate regression models, including the appropriate use and awareness of statistical assumptions underlying regression and the testing and refinement of such models. Dissertation (60 CATS) A dissertation of no more than 15,000 words on a topic relevant to social science research methods training. The thesis will involve either carrying out and reporting on a small social science research project which includes a full and considered description and discussion of the research methods employed or the discussion of a research issue or technique to a level appropriate for publication. OPTIONAL MODULES (all 10 CATS) We offer a range of specialist modules which reflect the teaching team’s diverse research interests, from the social logic of emotional life to conflict and change in divided societies, and specialist methods such as social science research online and visual research method. Optional modules generally run during the Spring semester and are offered subject to sufficient student demand and staff availability. Students will be able to choose a number of optional modules (depending on whether they are required to complete Quantitative Data Analysis: Foundational). Please check with the Programme Director for queries about specific modules. Advanced Qualitative Research Methods Building upon the core qualitative training, this module will explore one or more techniques of more advanced qualitative analysis. This may include such methods as ethnographic observation, interviewing, focus groups or biographical methods. Social Science Research Online The internet is a valuable tool in social science research - not just as a source of information but as a medium for recruiting research subjects and conducting research. This module looks at using the internet to find information, to identify populations and to conduct social research using methods such as online interviewing and online participant-observation. Advanced Quantitative Research Methods Building upon the core quantitative training, this module will explore one or more techniques of more advanced quantitative analysis. Students will have the opportunity to further develop their knowledge and understanding of quantitative research methods and its application in addressing key research questions, drawing on recent survey data. Conflict and Change in Northern Ireland: New Sociological Research The objectives of this module are to introduce advanced students to key issues in contemporary research on conflict and change in divided societies, using Northern Ireland as a case study. It will examine critical sociological debates about identity, ethnicity, inequality, and conflict management, and interrogate their usefulness in a Northern Irish context. Emphasis will be placed on how Northern Ireland may conform to, or challenge, contemporary debates in theoretical and comparative sociology. Researching Emotions and Social Life This course aims to examine research on the social logic of emotional life. Emotions are considered not as personal or 'inner' psychological phenomena, but as sociological processes. The course focuses on studies which illustrate, in varying ways, how emotions are elicited through, and in turn shape, social relations, as they provide evaluative responses to the operation of power and status. The course will consider a range of classic and contemporary, structuralist and interactional perspectives informing studies of specific emotions, including shame, anger and love. Algorithms and Society The module aims to provide students with some critical concepts to explore the role that technology such as algorithms play in various social domains and make sense of the new structures of power and order, their promise of security and the risks they involve. Thinking critically of how data are collected, used and how outputs are produced by new technologies will encourage students to look at issues such as biases, inequalities, and injustices engrained within the development and deployment technologies. We will also look at the complexities involved in investigating, analysing and assessing how technologies such as algorithms operate for a social scientist, and the challenge of interdisciplinary research.

Teaching Times

The programme is usually delivered in evenings and full day/half day sessions, including weekends.

Career Prospects

Introduction
Research skills are highly transferable and marketable, and needed across a range of sectors – academic, government, charities and business. MRes students receive excellent advanced training in both quantitative and qualitative research skills and gain experience of independent project management through the dissertation. Graduates can use their qualification to develop a career in any aspect of social research. The MRes is also ideal high-level preparation for doctoral research (PhD).

Queen's postgraduates reap exceptional benefits. Unique initiatives, such as Degree Plus and Researcher Plus bolster our commitment to employability, while innovative leadership and executive programmes help our students gain key leadership positions both nationally and internationally.

Employment after the Course
After graduation, students are well placed to continue on to doctoral research, applying their research skills to carry out an in-depth investigation of a particular topic. Past graduates have secured funded PhDs on a variety of topics, from cyber surveillance to educational inequality. Some students have moved into careers in social research or used their qualification to upskill in their current job, for example, in charities or government departments.

Employment Links
Social science research skills are useful in a range of sectors - academia, government, charities and business. Our graduates are working with a range of employers, from Barnardos to the Northern Ireland Statistics and Research Agency.

Learning and Teaching

Learning opportunities available with this course are outlined below:

Assessment

Assessments associated with this course are outlined below:

Facilities

The School is situated across a suite of three buildings in Belfast's Queen's Quarter. We provide student and staff common rooms, computer suites and designated study spaces.

Explore the teaching and social spaces in our School through our 360 Virtual Tour:
https://youtu.be/vB0jafwkgd0

The Graduate School
https://www.youtube.com/watch?v=aJ_BwOtjXAE

Resources

You can view a recent course webinar at the link below:
https://youtu.be/w9nMhGScfjc

Modules

• Year 1

  Core Modules

  Research Design (20 credits)

  ×

  Research Design

  Overview

  This module offers an introduction to quantitative and qualitative research methods and is designed for students with some basic knowledge but who seek further grounding. It is designed as preparation for undertaking postgraduate research and dissertation work. It also acts as preparation for the advanced quantitative and qualitative courses (SOC9060 and SOC9061).

  Learning Outcomes

  Students will acquire knowledge of how to develop research problems and of the principles of research design. They will have developed a critical awareness of alternative approaches to research. They will be able to comprehend and negotiate the ethical issues involved in research, including the uses of research and the social and political contexts of research. Students will develop a capacity to apply qualitative and quantitative methods to research problems and will understand the relationship between epistemological positions, theory and research design.

  Skills

  Skills acquired include: Ability to formulate testable hypotheses, research problems and questions. Knowledge of research resources including qualitative data sources, documentary data, statistical sources, textual and visual archives. Knowledge of how research data is collected.

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  20

  Module Code

  SOC9012

  Teaching Period

  Autumn

  Duration

  10 weeks

  Pre-requisite

  No

  Core/Optional

  Core

  Qualitative Data Analysis (10 credits)

  ×

  Qualitative Data Analysis

  Overview

  The course will provide students with an introduction to the knowledge necessary for the informed use of the qualitative data analysis software package NVivo 11. The course provides students with a base level introduction to the analytical and technical skills in qualitative data analysis appropriate to the production of a Master’s dissertation and/or use of CAQDAS software for social research purposes.

  Learning Outcomes

  • To introduce key skills in qualitative data management and analysis.
  • To provide students with an understanding of the benefits/limitations for a social researcher of using a qualitative data storage and analysis software package.
  • To introduce and develop the basic skills necessary for the computer aided analysis of qualitative data using the software package NVivo 11.

  Skills

  • Development of analytical and evaluative skills
  • Qualitative data analysis skills by using thematic analysis and computer software package NVIVO 11.

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9055

  Teaching Period

  Spring

  Duration

  1 weeks

  Pre-requisite

  No

  Core/Optional

  Core

  Quantitative Data Analysis: Foundational (10 credits)

  ×

  Quantitative Data Analysis: Foundational

  Overview

  The module provides an introduction to the basics of quantitative data analysis. It covers data manipulation techniques and students are introduced to a range of key statistical concepts. Univariate and bivariate statistical procedures are covered in the module. The module provides hands-on practical experience in the use of SPSS for the analysis of large and complex datasets. Students are trained in SPSS syntax (the SPSS programming language). The module is taught through a series of lectures and practical workshops. These two strands are interwoven within each teaching session. New material is presented in short bursts followed by an opportunity for students to apply the new learning to the teaching datasets. The learning outcomes align most closely with SDG 8 ‘Decent Work and Economic Growth’; the module prepares students for future jobs requiring analytical skills which fits with the increasing use of data to inform decision making at policy level.

  Learning Outcomes

  • Be familiar with the organisation and management of large complex quantitative datasets.
  • Be capable of undertaking basic statistical analysis using SPSS syntax.
  • Be capable of basic data manipulation techniques using SPSS syntax.

  Skills

  • Handling, managing and manipulating large and complex quantitative datasets.
  • Competency in SPSS programming syntax (basic level).
  • Basic statistical analysis and interpretation.
  • Preparation of quantitative analysis reports.

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9056

  Teaching Period

  Spring

  Duration

  5 weeks

  Pre-requisite

  No

  Core/Optional

  Core

  Quantitative Data Analysis: Intermediate (10 credits)

  ×

  Quantitative Data Analysis: Intermediate

  Overview

  The module will focus on multivariate regression models. Particular attention will be placed on the appropriate use of such procedures, awareness of the statistical assumptions underlying regression approaches and the testing and refinement of such models. The module will also cover a range of complex data manipulations. The module is taught through a series of seminars and practical workshops. These two strands are interwoven within each teaching session. New material is presented in short bursts followed by an opportunity to apply the new learning to the teaching datasets. The class size is relatively small, giving students opportunities for one-to-one work with the teaching staff.

  Learning Outcomes

  • Be familiar with the organisation and management of large complex quantitative datasets.
  • Be capable of undertaking multivariate regression analyses using SPSS syntax.
  • Be aware of the assumptions that underpin the application of regression models, how to test for violation of these assumptions and how to correct, where appropriate, for any violations detected.
  • Be capable of constructing a multivariate regression model and interpreting the SPSS output.

  Skills

  • Handling, managing and manipulating large and complex quantitative datasets.
  • Competency in SPSS programming syntax.
  • Multivariate statistical analysis and interpretation.
  • Preparation of quantitative analysis reports.

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9057

  Teaching Period

  Spring

  Duration

  5 weeks

  Pre-requisite

  No

  Core/Optional

  Core

  The Sources and Construction of Qualitative Data (10 credits)

  ×

  The Sources and Construction of Qualitative Data

  Overview

  This module explores the theoretical foundations of qualitative research, examining the relationship between theory and methods including different approaches to qualitative interviewing. The module also covers how to design and conduct qualitative interviews and focus groups.

  Learning Outcomes

  Learning Outcomes
  • Critically analyse the relationship between theoretical approaches and the conduct of qualitative social research
  • Demonstrate how questions of epistemology and ontology impact on qualitative research
  • Critically analyse the relationship between theory and methods in qualitative interviewing
  • Demonstrate how to design and conduct qualitative interviews and focus groups
  • Demonstrate reflexivity, including how to reflect critically on the researcher’s role in knowledge production

  Skills

  Ability to demonstrate link between theory and methods through practical application.
  Ability to critically evaluate research using qualitative methods
  Ability to practically recognise epistemological and ontological factors in relation to specific examples
  Ability to recognise how qualitative research differs from quantitative research
  Ability to articulate the strengths and weaknesses of qualitative research
  Ability to critically evaluate journal articles based on qualitative research

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9053

  Teaching Period

  Autumn

  Duration

  1 weeks

  Pre-requisite

  No

  Core/Optional

  Core

  The Sources and Construction of Quantitative Data (10 credits)

  ×

  The Sources and Construction of Quantitative Data

  Overview

  The aim of the course is to provide a comprehensive overview of the theory and practice of measurement and constructing quantitative data in the social sciences. Through lectures and practical exercises, students will develop relevant knowledge of key data sources in the social sciences, their respective uses and usefulness, and their relevance for the study of contemporary social issues. The range of subjects across the social sciences that are measured with quantitative data is very broad and the content of the module will need to be selective. The module will in particular cover topics related to concepts in the social science (e.g. poverty, the welfare state) which have spurred lively debates in the discipline with regard to the analytical and methodological approaches which can be used to measure them.

  Learning Outcomes

  •Understand key concepts of quantitative analysis and measurement (conceptualization, operationalization, indicators, sampling, reliability, validity, index construction)
  • Be able to locate, transform and interpret different data sources that can be used to measure and address substantive issues in the social sciences.
  Become a confident user of secondary data and be able to critically assess its relevance, quality and validity in relation to research design and aims
  •Critically evaluate published social science research using quantitative data and statistical methods
  • Be able to identify the strengths and weaknesses of this style of research

  Skills

  • Identifying relevant statistical sources
  • Extracting and manipulating secondary data
  • Evaluating surveys and other secondary data
  • Problem analysis and problem solving

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9054

  Teaching Period

  Autumn

  Duration

  2 weeks

  Pre-requisite

  No

  Core/Optional

  Core

  Theory and Debates in Social Research (20 credits)

  ×

  Theory and Debates in Social Research

  Overview

  This module aims to deepen students’ understanding of key contemporary debates in social theory and research, providing advanced-level teaching for those building upon basic knowledge and undertaking postgraduate research. It is designed to demonstrate and explore how social theory is utilised, critiqued and developed through the pursuit of social research. There will be a particular focus upon the epistemological positions that underpin different viewpoints in these debates, and upon points of similarity and difference between these viewpoints. The overall aim is that students will gain a deeper understanding of some key social theories and concepts, and will see the ongoing and iterative relationship between theory and the practice of research.

  Learning Outcomes

  Students will gain a deeper understanding of debates that have played a key role in contemporary social theory, research and practice, developing an awareness of the different perspectives in these debates and the ways in which arguments are constructed, defended and critiqued. The way in which these debates have been developed in social research will be highlighted through attention to empirical studies and by encouraging reflection by students upon their own studies and research. Students will develop a capacity to make connections between different debates and to compare the different epistemological positions that underpin these.

  Skills

  Skills developed include: analysing, evaluating and interpreting debates; developing and defending reasoned opinions; developing and demonstrating independent thinking; critically reflecting upon one’s own studies and research.

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  20

  Module Code

  SOC9024

  Teaching Period

  Autumn

  Duration

  10 weeks

  Pre-requisite

  No

  Core/Optional

  Core

  Dissertation (60 credits)

  ×

  Dissertation

  Overview

  A dissertation of approximately 15,000-20,000 words on a topic relevant to social science research methods training. The thesis will deal with either carrying out and reporting a small social research project which includes a full and considered description and discussion of the research methods employed or the discussion of a research issue or technique to a level appropriate for publication.

  Learning Outcomes

  The demonstration of competence in a given method of social research.

  Skills

  Time management, developing a comprehensive knowledge of a broad topic area; reviewing literature, marshalling and presenting an argument; research design; summarising research findings and relating these to concepts.

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  60

  Module Code

  SOC9019

  Teaching Period

  Full Year

  Duration

  24 weeks

  Pre-requisite

  No

  Core/Optional

  Core

  Optional Modules

  Algorithms and Society (10 credits)

  ×

  Algorithms and Society

  Overview

  Our societies have become increasingly technological: the use of Internet, the pervasiveness of social media. In many institutional and non-institutional contexts, algorithms are relied upon to capture and regulate much of our life, indicating the need to think critically about transformations in our social world. What sort of social relations emerge as a result of the use of these new tools? What sort of ordering do they produce? This module aims to provide students with a critical understanding of how some of these new developments operate in the social world. Technologies, however, should not be studied just as structures producing specific material consequences. They should also be viewed from a sociological perspective to understand the ways they are shaped by the specific contexts within which they are designed; we should look at the various cultural assumptions implicated in these designs, as well as the world they make us imagine. Each of us is scrutinized by countless algorithms every day without realizing it. What role do they play in making us knowable? With what effects? Algorithms as new technologies affect the structure of our social order, shape our sense of self, sense of community, and forms of relationships, constituting new tools to govern society, provide data, and, crucially, to produce knowledge about us. They are continuously deployed in multiple domains as magic bullets to realize efficiency and speed.
  The module will question the role technology such as algorithm plays in various domains and provide some critical and theoretical understanding for students to make sense of the new structures of power and order, their promise of security and the risks they involve. By doing so, the module clearly addresses goal number 9 of the UN Sustainable Development Goals: Industry, Innovation and Infrastructure and interjects into goal 16 on Peace Justice and Strong Institutions. It aims to critically look at the ways technologies are increasingly deployed as part of and by our institutions in the unfolding of our lives (increasingly so since the global covid-19 pandemic). It considers ways the deployment of technologies may be made more transparent and queries the possible pernicious effects they may have. Thinking critically of how data are collected and used by new technologies will address possible biases, inequalities, and injustices in the deployment of these technologies.

  Learning Outcomes

  The module will cover some core general theories on technology and society to enable critical question on the ways specific technologies- and algorithms in particular- are produced. It will provide an opportunity for students to apply some of these theories to different contexts. The module may consider different technology/contexts/case studies on which to apply some of the social theories on technological development.
  By the end of the module, students will be able to:
  - Understand the role of technology such as the algorithm within Internet, especially social media;
  - Identify technology such as the algorithm as a ‘black box’, understanding the ways social, cultural and political factors influence the ways algorithms are shaped;
  - Understand technology such as the algorithm as a ordering tool to sort people into categories according to race, gender, income, health, etc., thus determining their criminal propensities;
  - Reflect on methodologies to investigate, analyse, and assess the ways technologies and algorithms are constructed and operate, their effects on society, both positive and negative, and the opportunities and difficulties of inter-disciplinarity that this effort may involve.

  Skills

  On completion of the module, students will be able to:
  -Understanding what Artificial Intelligence is – and how it is constructed.
  
  - Consider the role of technology in contemporary world
  
  - Reflect on methodologies to research AI
  
  - Understand the implications of AI within society, and its harms

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9071

  Teaching Period

  Spring

  Duration

  5 weeks

  Pre-requisite

  No

  Core/Optional

  Optional

  Conflict and Change in Northern Ireland: New Sociological Research (10 credits)

  ×

  Conflict and Change in Northern Ireland: New Sociological Research

  Overview

  This module demonstrates the unique insights to be offered by sociological research on Northern Ireland’s transition from conflict through detailed case studies of ongoing research projects. These will cover topics such as: demographic change, attitudinal change, socio-economic change and inequalities, dealing with the legacy of conflict, and ‘culture wars’. The purpose of the module is to introduce students to the benefits of a sociological approach to the subject and to the challenges of conducting sociological research in a society in transition.

  Learning Outcomes

  • Students will gain knowledge and understanding of sociological approaches to contemporary society in Northern Ireland, particularly in relation to its transition out of conflict
  • Students will be able to critique and assess the value of various methods in sociological research
  • Students will be familiar with the core social trends and changes in contemporary society in Northern Ireland, particularly those relating to the process of transition from conflict
  • Knowledgeable of sociological debates around conflict and change in Northern Ireland in particular and divided societies in general.
  • Able to relate different sociological concepts to the empirical research on Northern Ireland.
  • Able to effectively gather, retrieve and synthesise different types of information to evaluate the module’s themes.

  Skills

  Academic skills:
  • An ability to critically read and evaluate sociological literature and non-academic/media material on contemporary Northern Ireland
  • An ability to collect and interpret evidence about contemporary society in Northern Ireland
  • An ability to demonstrate evidence of independent thinking and to compose reasoned opinions based on development of thought and knowledge
  • An ability to relate sociological concepts to the empirical study of Northern Ireland.
  Practical skills:
  • An ability to write in a clear, structured and critical manner using a range of source material
  • An ability to present information in spoken form and to contribute to discussions
  • An ability to retrieve and synthesise primary and secondary, quantitative and qualitative, sources of (print and electronic) information
  • An ability to use information technology to gather, organise and evaluate material

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9062

  Teaching Period

  Spring

  Duration

  5 weeks

  Pre-requisite

  No

  Core/Optional

  Optional

  Inequality and Emotions (10 credits)

  ×

  Inequality and Emotions

  Overview

  This course aims to examine research on the social logic of emotional life. Emotions are considered not as personal or ‘inner’ psychological phenomena, but as sociological processes. The course focuses on studies which illustrate, in varying ways, how emotions are elicited through, and in turn shape, social relations, as they provide evaluative responses to the operation of power and status. The course will consider a range of classic and contemporary, structuralist and interactional perspectives informing studies of specific emotions, including shame, anger and love.

  Learning Outcomes

  On successful completion of this course students will be equipped to
  • understand of the significance of emotions in contemporary social life;
  • evaluate competing perspectives on the logic of social emotions
  • critically analyse specific emotional orientations and responses.

  Skills

  • reviewing academic literature;
  • devising research problems;
  • analysing, evaluating and interpreting research materials;
  • developing and defending reasoned arguments;
  • developing and demonstrating independent thinking

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9058

  Teaching Period

  Spring

  Duration

  5 weeks

  Pre-requisite

  No

  Core/Optional

  Optional

  Qualitative Research with Children and Young People (10 credits)

  ×

  Qualitative Research with Children and Young People

  Overview

  This module introduces students to some of the key qualitative approaches to carrying out research with children and young people and the realities and practicalities in doing so. The module begins by introducing the main issues and dilemmas in qualitative research with children and young people and moves on to critically interrogate the notion of participatory research. The adaption of ‘traditional methods’ of data collection is discussed alongside methods specifically designed to ‘engage’ children and young people in the research process. The strengths and weaknesses of various methods are discussed and each is illustrated through research examples. Practical tips in designing and ‘doing’ qualitative research are built into the sessions.

  Learning Outcomes

  On successful completion of the module, students will be able to:
  • Evaluate the strengths and weaknesses of a range of research methods used to gain the views and experiences of children and young people;
  • Critically evaluate the meaning of participatory research;
  • Demonstrate understanding of some of the practical and methodological issues in carrying out qualitative research with children and young people;
  • Design a piece of qualitative research to elicit the views of children and young people.

  Skills

  Students will be engaged in processes allowing them to:
  • Apply theory and learning to practical/ research examples
  • Develop skills in the critical evaluation of various research methods
  • Assess appropriate methods for carrying out research with children and young people
  • Design a sample piece of research with children and young people
  • Develop oral skills through participation in tutorials and group work tasks
  Develop skills in digital literacy through online interactive activities and taking part in discussion forums
  • Develop an ability to write in a clear, structured and critical manner utilising a wide range of source material

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9049

  Teaching Period

  Spring

  Duration

  1 weeks

  Pre-requisite

  No

  Core/Optional

  Optional

  Social Science Research On-line (10 credits)

  ×

  Social Science Research On-line

  Overview

  The internet is a valuable tool in social science research - not just as a source of information but as a medium for recruiting research subjects and conducting qualitative research. This course looks at using the internet to find information, to identify populations and to conduct sociological research using methods such as on-line interviewing and on-line participant-observation.

  Learning Outcomes

  To develop on-line research skills. To develop knowledge of the strengths and weaknesses of social science research conducted in an on-line environment.

  Skills

  On-line interviewing, on-line participant observation and on-line ethnography. General IT skills. Evaluation of on-line data and on-line research methods. Identification of and access to hard-to-reach populations.

  Coursework

  100%

  Examination

  0%

  Practical

  0%

  Credits

  10

  Module Code

  SOC9023

  Teaching Period

  Spring

  Duration

  5 weeks

  Pre-requisite

  No

  Core/Optional

  Optional

Entrance requirements

Graduate
Normally a 2.1 Honours degree or above or equivalent qualification acceptable to the University in a social science or related discipline.

Applicants holding a 2.1 Honours degree in a non-related discipline may be considered if they have at least two years of professional experience in a relevant context.

Closing date for applications: Monday 31st July 2023 at 4pm.

Late applications may be considered.

Applicants are advised to apply as early as possible. In the event that any programme receives a high number of applications, the University reserves the right to close the application portal prior to the deadline stated on course finder. Notifications to this effect will appear on the Direct Application Portal against the programme application page.

International Students

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English Language Requirements

Evidence of an IELTS* score of 6.5, with not less than 5.5 in any component, or an equivalent qualification acceptable to the University is required. *Taken within the last 2 years.

International students wishing to apply to Queen's University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.

For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.

Career Prospects

Introduction
Research skills are highly transferable and marketable, and needed across a range of sectors – academic, government, charities and business. MRes students receive excellent advanced training in both quantitative and qualitative research skills and gain experience of independent project management through the dissertation. Graduates can use their qualification to develop a career in any aspect of social research. The MRes is also ideal high-level preparation for doctoral research (PhD).

Queen's postgraduates reap exceptional benefits. Unique initiatives, such as Degree Plus and Researcher Plus bolster our commitment to employability, while innovative leadership and executive programmes help our students gain key leadership positions both nationally and internationally.

Employment after the Course
After graduation, students are well placed to continue on to doctoral research, applying their research skills to carry out an in-depth investigation of a particular topic. Past graduates have secured funded PhDs on a variety of topics, from cyber surveillance to educational inequality. Some students have moved into careers in social research or used their qualification to upskill in their current job, for example, in charities or government departments.

Employment Links
Social science research skills are useful in a range of sectors - academia, government, charities and business. Our graduates are working with a range of employers, from Barnardos to the Northern Ireland Statistics and Research Agency.

Additional Awards Gained(QSIS ELEMENT IS EMPTY)

Prizes and Awards(QSIS ELEMENT IS EMPTY)

Graduate Plus/Future Ready Award for extra-curricular skills

In addition to your degree programme, at Queen's you can have the opportunity to gain wider life, academic and employability skills. For example, placements, voluntary work, clubs, societies, sports and lots more. So not only do you graduate with a degree recognised from a world leading university, you'll have practical national and international experience plus a wider exposure to life overall. We call this Graduate Plus/Future Ready Award. It's what makes studying at Queen's University Belfast special.

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Entry requirements

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Fees and Funding

Tuition Fees

Northern Ireland (NI) 1	£6,980
Republic of Ireland (ROI) 2	£6,980
England, Scotland or Wales (GB) 1	£8,360
EU Other 3	£19,100
International	£19,100

¹ EU citizens in the EU Settlement Scheme, with settled status, will be charged the NI or GB tuition fee based on where they are ordinarily resident. Students who are ROI nationals resident in GB will be charged the GB fee.

² EU students who are ROI nationals resident in ROI are eligible for NI tuition fees.

³ EU Other students (excludes Republic of Ireland nationals living in GB, NI or ROI) are charged tuition fees in line with international fees.

All tuition fees quoted are for the academic year 2023-24, and relate to a single year of study unless stated otherwise. Tuition fees will be subject to an annual inflationary increase, unless explicitly stated otherwise.

More information on postgraduate tuition fees.

Additional course costs

All Students

Depending on the programme of study, there may be extra costs which are not covered by tuition fees, which students will need to consider when planning their studies.

Students can borrow books and access online learning resources from any Queen's library. If students wish to purchase recommended texts, rather than borrow them from the University Library, prices per text can range from £30 to £100. Students should also budget between £30 to £75 per year for photocopying, memory sticks and printing charges.

Students undertaking a period of work placement or study abroad, as either a compulsory or optional part of their programme, should be aware that they will have to fund additional travel and living costs.

If a programme includes a major project or dissertation, there may be costs associated with transport, accommodation and/or materials. The amount will depend on the project chosen. There may also be additional costs for printing and binding.

Students may wish to consider purchasing an electronic device; costs will vary depending on the specification of the model chosen.

There are also additional charges for graduation ceremonies, examination resits and library fines.

Social Science Research costs

There are no specific additional course costs associated with this programme.

How to Apply

Apply using our online Postgraduate Applications Portal and follow the step-by-step instructions on how to apply.

Apply now

Terms and Conditions

The terms and conditions that apply when you accept an offer of a place at the University on a taught programme of study.
Queen's University Belfast Terms and Conditions.

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Download Postgraduate Prospectus