This programme provides practical, career-orientated training in social science research methods, including research design, data collection and data analysis relating to both qualitative and quantitative modes of inquiry.
Students will have the opportunity to specialise in particular methodologies and to learn more about the application of these methodologies to illuminate important issues and debates in contemporary society.
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.
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 empirical research projects. The module will also explore issues around the ethics of social science research as well as the connection between social science research and policy concerns. It is designed as preparation for undertaking postgraduate research and dissertation work.
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 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. The role of different types of interviewing in qualitative research will be utilised in order to explore the relationship between theory and methods.
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
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.
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.
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.
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.
We offer a range of advanced modules in quantitative and qualitative research methods, for example, logistic regression, internet-based research and visual research methods. We also provide 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. 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 maximum of three to four option modules (depending on whether they need to complete Quantitative Data Analysis: Foundational). Please note that it is unlikely that all the following modules will be available for 2017/8. Please check with the Programme Director for queries about specific modules.
Semantic Technologies is a relatively new term that describes all areas concerned with using and developing software and methodologies for meaning-centred manipulation of information. The aim is to provide software and methodologies so that web resources, data in databases and raw data associated with programs can be processed and manipulated in a more intelligent way. This requires storing, understanding, manipulating and reasoning about the meaning of the data. Semantic technologies are increasingly being used in such varied applications as the semantic web, health care and biomedical domains, the life sciences, software/hardware industries and the automotive industry.
The Semantic Technologies pathway combines themes such as 'Data on the Web' with 'Ontology Engineering and Automated Reasoning'. These core offerings can be combined with any other theme. Good complementary themes are Data Engineering, Managing Data, Learning from Data, Security and Software Engineering.
Computational thinking is becoming increasingly pervasive and is informing our understanding of phenomena across a range of areas; from engineering and physical sciences, to business and society. This is reflected in the way the Manchester course is taught, with students able to choose from an extremely broad range of units that not only cover core computer science topics, but that draw on our interdisciplinary research strengths in areas such as Medical and Health Sciences, Life Sciences and Humanities.
Lectures and seminars are supported by practical exercises that impart skills as well as knowledge. These skills are augmented through an MSc project that enables students to put into practice the techniques they have been taught throughout the course.
Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: [email protected]
Students following the Semantic Technologies pathway have all the career choices and options as described for general Advanced Computer Science.
In addition, students of this pathway are ideally placed to work in software companies or for healthcare providers who are using or developing Semantic Technologies.
We maintain close relationships with potential employers and run various activities throughout the year, including career fairs, guest lectures, and projects run jointly with partners from industry. This is managed by our Employability Tutor; see the School of Computer Science's employability pages for more information.
This programme is CEng accredited and fulfils the educational requirements for registration as a Chartered Engineer when presented with a CEng accredited Bachelors programme.
At the Centre for Intelligent Systems and their Applications (CISA) we enable computer systems to reproduce or complement human abilities, work with people, and support collaboration between humans. We conduct world-leading research in the foundations of Artificial Intelligence (knowledge representation and reasoning, emergence of meaning, theory and ontology change, creativity, mathematical proof) and in intelligent collaborative systems (multiagent systems, social computation, scientific collaboration platforms, web semantics and linked data).
Our research methods are inspired by developing formal models of knowledge, reasoning, and interaction that can be used to understand and automate aspects of human intelligence, but are also understandable and usable to the human designers and users of AI systems.
To achieve this, we combine theoretical research into computational models, architectures, and algorithms with a strong element of applied research. This has led to a strong track record in using our methods to address real-world problems in healthcare, scientific collaboration, social computing, emergency systems, transportation, engineering, aerospace and others.
You'll find a wide range of research areas within CISA conducted in the four research groups the Institute currently hosts:
CISA includes one of the most innovative collaborations between research and business - our Artificial Intelligence Applications Institute (AIAI). Through its resources and the engagement of CISA staff and students in consultancy, training and joint projects, we help companies and government agencies to apply newly researched techniques.
You will carry out research work within a research group under the guidance of a supervisor. You may also attend taught courses that are relevant to your research topic, as prescribed by your supervisor. You will be expected to attend seminars and meetings of relevant research groups. Periodic reviews of progress are conducted to assist with research planning.
A programme of transferable skills courses facilitates broader professional development in a wide range of topics, from writing and presentation skills to entrepreneurship and career strategies.
The School of Informatics holds a Silver Athena SWAN award, in recognition of our commitment to advance the representation of women in science, mathematics, engineering and technology. The School is deploying a range of strategies to help female staff and students of all stages in their careers and we seek regular feedback from our research community on our performance.
The award-winning Informatics Forum is an international research facility for computing and related areas. It houses more than 400 research staff and students, providing office, meeting and social spaces.
It also contains two robotics labs, an instrumented multimedia room, eye-tracking and motion capture systems, and a full recording studio amongst other research facilities. Its spectacular atrium plays host to many events, from industry showcases and student hackathons to major research conferences.
Nearby teaching facilities include computer and teaching labs with more than 250 machines, 24-hour access to IT facilities for students, and comprehensive support provided by dedicated computing staff.
Among our entrepreneurial initiatives is Informatics Ventures, set up in 2008 to support globally ambitious software companies in Scotland and nurture a technology cluster to rival Boston, Pittsburgh, Kyoto and Silicon Valley.
While your research studies are a perfect route to a career in academia, your degree could also take you into the commercial world of applied AI and collaborative systems.
Software developers using AI technologies are among those who rely on the insights of our research. NASA and animation company Pixar are just two of the organisations that have recently employed our graduates.
This course is designed for computer science, informatics and IT professionals who want to pursue a career in which advanced research skills may be useful. It is most suitable for experienced or emerging professionals and is ideal if you wish to advance your knowledge of business performance and how it is supported by information technology.
What you study
The course is structured to give you advanced level research skills specifically relevant to the IT discipline, together with a framework for developing your knowledge of how organisations seek to use IT for transformation and innovation.
On the course you examine the relationships between corporate strategy, business models, services and process models, performance, risk and value management, and computer technology. You discover how enterprise systems can be integrated with strategic and tactical business decision-making as well as data analytics and processing. You also learn about emergent technologies such as smart applications driven by artificial intelligence and robotic process automation.
Throughout your work, questions will emerge and you will be able to identify topics to research based on what you have studied. You take three modules that reflect your area of specialism or that provide you with important background knowledge. You also learn about research techniques from which you conduct your preliminary research study and dissertation.
Throughout the course you benefit from a strong underpinning focus on computer science and informatics.
The course has been designed in consultation with LEADing Practice, an Enterprise Standards body whose models are integrated into enterprise software products of SAP™, IBM™, iGrafx™ and LEADing Practice’s Enterprise+. This professional, vendor-neutral standards body brings to bear its invaluable experience to the course, having worked with over 4,600 industry practitioners.
In addition, you are taught by leading research-active academics and industrial practitioners. Eminent contributors and guest speakers enhance your learning by exposing you to theoretical knowledge and real-world case studies. This may include industry professionals such as the founder of Enterprise Architecture, John A. Zachman. Further support comes from the Global University Alliance (GUA), a consortium with more than 450 academic institutions in its membership. Both LEADing Practice and the GUA work with other standards bodies such as the OMG, ISO, IEEE, CEN, and W3C. All this knowledge is uniquely brought together in this course to provide you with industry expertise and connections.
As a result the course helps to raise your professional profile with your existing or prospective employer and enables you to pursue a career where advanced research skills are may be useful, including those appropriate for doctoral study.
The course is designed as study blocks so that you attend for two weeks in October then two weeks in January in the academic year. The remaining time you engage in pre-reading, and work on your assessments including a preliminary research study and your research dissertation.
you then undertake the following two modules in which you engage with your agreed research topic with close supervision
On completion of the course you should be able to demonstrate the most relevant ways that computers can help organisations achieve their goals.
You may aim to pursue studies at PhD level, or develop your skills as an industrial practitioner in enterprise modelling, engineering or architecture.
You can join the LEADing Practice open source standard development community – more than 4600 practitioners who work across all sectors of industry. The MRes enables you to become certified as a LEAD Transformation eXpert as well as a LEAD Business Architect.
With such a wide variety of options, you can expect a fulfilling career leading to a senior technological or business role.
This course is perfect if you are looking to embark on a successful career as a researcher or academic and will provide you with the necessary training as part of your study for your MPhil/PhD.
The course is distinctive in providing students with an exciting opportunity to develop expertise in a range of both quantitative and qualitative research methods of data collection and analysis with a focus on their application to real-world issues.
The course has 1+3 recognition from the Economic and Social Research Council. Only three Education Departments in post-92 universities have this prestigious kitemark.
In order to enhance your engagement with the issues to be examined, and to allow flexibility over how you manage your time, the Social Research Methods programme will be delivered through weekly sessions in the Autumn and Spring semesters supplemented by tutorial support available (both face-to-face and electronically). Evening sessions are provided for part-time students.
All three levels of the programme will include an introduction to the processes and issues involved in designing a quantitative or qualitative research project. You will also undertake modules that will introduce you to the methods of quantitative (including use of SPSS) and qualitative (including use of CAQDAS) research, giving you the skills and confidence to use these approaches to data collection and analysis in your own research.
If you progress to do a PGD or MA you will also explore the philosophy of social science research where you will examine the relationship between epistemology, ontology and methodology. Furthermore, you will explore concepts that underpin educational and social research including empiricism, rationalism, hermeneutics, feminism, post-modernism and critical realism and critique their relation to objectivity, causation, and validity.
You will also focus on key elements of the Research Councils’ Joint Statement of Skills Training for Research Students. You can then choose to study interpretations of the concept of education - and their implications for research - and the role of values in educational theory and research methodologies, or the basic theoretical concepts in social theory, with a particular emphasis on sociology and social policy.
Masters students will complete a dissertation in an area of their choosing in the fields of education or the social sciences.
The PG certificate course addresses core features of social research methods, focusing on different forms of data and how they can be collected and analysed. MA-level study is aimed at students who either want a discrete research-based MA or want to run a pilot study for an MPhil/PhD research project.
The following is a list of modules that you need to take to complete the different awards:
All of the PGC modules and
plus one of two optional modules:
All of the PGD modules and
Compulsory and Required modules
Compulsory and/or required modules may change when we review and update programmes. Above is a list of modules offered this academic year.
Optional modules, when offered as part of a programme, may vary from year to year and are subject to viability.
This is THE course for those wishing to be employed in the research field of education and/or social sciences.
The MSc Computer Science is an advanced programme for graduates and professionals. It focuses on the latest techniques and technologies, teaching you how to apply these to complex contemporary problems across the breadth of society.
You will be able to engage with the latest developments from a range of Computer Science topics with leading academics in the field. Course content draws directly upon our particular research strengths in artificial intelligence, machine learning, data science, high performance computing and networks, and cyber-security.
This MSc is career-focused, with an emphasis on postgraduate training. You will develop a wide range of important skills such as team-working, coding, independent research and problem solving. This course is particularly suited to those looking to continue in academia or use their expertise commercially in any sector.
Constituent modules and pathways may be updated, deleted or replaced in future years as a consequence of programme development. Details at any time may be obtained from the programme website.
The compulsory modules can include;
Optional modules can include;
Assessment methods include essays, closed book tests, exercises in problem solving, use of the Web for tool-based analysis and investigation, mini-projects, extended essays on specialized topics, and individual and group presentations.