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Cambridge Research Methods

Cambridge Research Methods (CaRM) course timetable

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Tue 18 Mar – Wed 14 May

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Tuesday 18 March

11:00
Research Data Security (LT) new (2 of 2) In progress 11:00 - 12:00 CaRM Zoom

This course covers basic security for all your research data. In this course, research data means research files, folders, programs, participation sheets, notes, audio recordings, databases, spreadsheets, videos, transcripts, collaborations, datasets, agreements, diagrams, images, etc. that have value to you and your research. It is not just about personal data.

Part 1 introduces students to some of the legal issues around academic research involving personal data.

Parts 2, 3 and 4 cover basic information and cyber security, a quick impact assessment specifically for researchers and then covers the full risk assessment process by walking you through securing your research by conceptualizing and then assessing possible risks, followed by examining different ways to reduce those risks.

This is delivered in a practical and non-technical way although there are some terms to do with risk assessment which may be unfamiliar to you. For this reason there is a glossary available.

14:00
Decoloniality in Social Science Research Methods Part 2: Workshop 2 new [Places] 14:00 - 16:00 University Centre, Hicks Room

This is the second in a series of three workshops, which extend last term's teaching on 'Decoloniality in Research Methods'. In each session, participants will be presented with a range of theoretical concepts as well as case studies from a variety of scholars who mobilise these concepts to shape their methodologies. At least half of each session will be dedicated to practical application – participants will be encouraged to engage in a range of individual and group reflections, discussions and exercises.

Participants will be encouraged to reflect on how decolonial thought affects each stage of their research project. Beginning with initial research design and literature reviews, and ending with dissemination and research impact, each session focuses on a different stage in the research cycle, bringing a range of decolonial thought and scholar-activism into conversation with our research methods. Please note: Participants can choose whether to attend a single session or multiple sessions, as each will be a 'stand alone' workshop. However, each workshop must be booked separately.

Session 2: The role of ‘the researcher’ & the importance of reflexivity

In this session, we’ll discuss the notion of ‘reflexivity’, considering our disciplines, our roles as researchers within the University, and our experiences as individual researchers with our own life experiences and histories. We’ll then explore seven commonly used research methods (the development of ‘social theory’, quantitative analysis, ethnography, autoethnography, qualitative interviews, digital methods and archival research). We’ll ask what happens to these methods when we place them into a wider frame of decolonial analysis and look to other scholars who are using these methods to advance the goals of decolonization.

In terms of practical skills, participants will be encouraged to bring their own reflexive writing to the session, and we’ll explore how different theories relating to standpoint, positionality and intersectionality help us make sense of the approaches we are taking. Participants will be encouraged to bring an outline of their research methods and will work in thematic groups to place their methods in conversation with decolonial thought.

Wednesday 19 March

14:00
Decoloniality in Social Science Research Methods Part 2: Workshop 3 new [Places] 14:00 - 16:00 University Centre, Cormack Room

This is the third and last in a series of three workshops, which extend last term's teaching on 'Decoloniality in Research Methods'. In each session, participants will be presented with a range of theoretical concepts as well as case studies from a variety of scholars who mobilise these concepts to shape their methodologies. At least half of each session will be dedicated to practical application – participants will be encouraged to engage in a range of individual and group reflections, discussions and exercises.

Participants will be encouraged to reflect on how decolonial thought affects each stage of their research project. Beginning with initial research design and literature reviews, and ending with dissemination and research impact, each session focuses on a different stage in the research cycle, bringing a range of decolonial thought and scholar-activism into conversation with our research methods.

Please note: Participants can choose whether to attend a single session or multiple sessions, as each will be a 'stand alone' workshop. However, each workshop must be booked separately.

Session 3: From data collection to analysis to dissemination

In this session, we’ll begin with Linda Tuhiwai Smith’s (2012:226) claim that researchers ‘must get the story right as well as tell the story well’. We’ll think about what it means to analyse our data and create a product (a dissertation, research paper) which exists within the wider context of the academy. We’ll examine six different ways in which different researchers have oriented themselves towards their research, and their research towards the future (including an ‘ethics of care’, ‘rage anger and complaint’, ‘love, empathy, solidarity and desire’ and ‘action, speculation and movement’).

In terms of practical skills, we’ll think about our research outputs, the potential impacts of their design and dissemination and how these considerations might impact the earlier stages of our research projects, such as in the way we collect and store our data. Participants will also be encouraged to think about their own research orientation and place their project into a wider speculative context.

Coding in Qualitative Data Analysis (LT) new (2 of 2) In progress 14:00 - 16:00 University Centre, Hicks Room

Researchers often feel overwhelmed by large amounts of qualitative data, wondering how to organize and analyse it, and use it effectively as primary research evidence. This module introduces principles and methods of sense-making, helping researchers identify and understand the patterns, themes, and meanings embedded in their data.

The module consists of a comprehensive lecture and two hands-on workshops. Session 1 introduces the basic principles and methods, focusing on the progression from data to sense-making, how to relate data to existing literature, and how to construct a well-supported argument based on the empirical evidence. The two workshops are designed for students to experience and practice coding (manually or using software) and to develop their own arguments. In Session 2, students can apply sense-making techniques to their own data and practice interpreting data to draw meaningful insights manually. Session 3 focuses on data analysis using Atlas.ti software, which allows students to practise coding, categorising, and conceptualising their own empirical data or open-sourced datasets.

Sessions:

Session 1: Lecture: Analysing and interpreting qualitative data

Session 2: Practical workshop: Making sense of data

Session 3: Practical workshop: Software coding demonstration

Please note that Sessions 1 and 2 will be held on the same day (Wednesday 12 March 2025).

Thursday 20 March

10:00
Equitable Research through Creative Methods new (3 of 3) CANCELLED 10:00 - 12:00 CaRM Zoom

Research proposals, written consent forms, participant information sheets, letters of intent, briefs and proposals on university headed paper are all claims to power, neutrality and control in the research process. Though ethically imperative, this course is an opportunity to reflect upon these “fetishes of consent” (Wynn and Israel, 2018) and the unequal power relations they may produce between participant and researcher. Employing creative methods within the research process, from start to end, is an opportunity to communicate meaningfully with all stakeholders; from a struggling mother with low literacy levels in a Mumbai slum, to a time conscious policy official in Cape Town who refuses to glance past the first paragraph of your research proposal. The ability to communicate complex and often abstract ideas beyond an academic audience is pivotal to doing research with impact, and it is also a vital part of a decolonial agenda. While “the proof of the [decolonial] pudding” is arguably identified in how research is analysed and presented (Hitchings and Latham, 2020:392), it is crucial that methodologies are subject to critical reflexivity, and foster knowledge exchange between scholars, practitioners, and respondents.

In this course we will explore a variety of “creative methods” that have been developed for use in the field, and to generate empirical data. This course then goes further, to explore ways of incorporating creativity throughout the research process in areas such as stakeholder engagement, participant recruitment, consent processes, and gatekeeper conflict during data collection and research dissemination. As part of the course, you will make a simple means for creative outreach such as a video, presentation, drawing, or video recording (etc.) that communicates your research to intended stakeholder(s). We will think critically about intended audience demographics (i.e. elderly, working mothers, young people, peasant farmers, NGO workers or city officials) and reflect upon the creative materials we have produced as a group and discuss its methodological implications. The goal is not to use creative practice as simply another empirical data gathering tool, but to address the hierarchies within academic processes and knowledge production. Creative practice is an opportunity to build new communication strategies that foster the reflexivity, flexibility, and wonder of the unknown within co-production, enabling us to move towards more equitable ways of building and cocreating knowledge.

Tuesday 29 April

11:00
Doing Qualitative Interviews (ET) (1 of 3) [Places] 11:00 - 11:30 CaRM Zoom

Face-to-face interviews are used to collect a wide range of information in the social sciences. They are appropriate for the gathering of information on individual and institutional patterns of behaviour; complex histories or processes; identities and cultural meanings; routines that are not written down; and life-history events. Face-to-face interviews thus comprise an appropriate method to generate information on individual behaviour, the reasons for certain patterns of acting and talking, and the type of connection people have with each other.

The first session provides an overview of interviewing as a social research method, then focuses on the processes of organising and conducting qualitative interviews. The second session explores the ethics and practical constraints of interviews as a research method, particularly relevant when attempting to engage with marginalised or stigmatised communities. The third session focuses on organisation and analysis after interviews, including interpretation through coding and close reading.

In Easter Term, the course is entirely virtual, comprising the online resources, supported by 3 x zoom Q&A sessions.

Tuesday 6 May

11:00
Doing Qualitative Interviews (ET) (2 of 3) [Places] 11:00 - 11:30 CaRM Zoom

Face-to-face interviews are used to collect a wide range of information in the social sciences. They are appropriate for the gathering of information on individual and institutional patterns of behaviour; complex histories or processes; identities and cultural meanings; routines that are not written down; and life-history events. Face-to-face interviews thus comprise an appropriate method to generate information on individual behaviour, the reasons for certain patterns of acting and talking, and the type of connection people have with each other.

The first session provides an overview of interviewing as a social research method, then focuses on the processes of organising and conducting qualitative interviews. The second session explores the ethics and practical constraints of interviews as a research method, particularly relevant when attempting to engage with marginalised or stigmatised communities. The third session focuses on organisation and analysis after interviews, including interpretation through coding and close reading.

In Easter Term, the course is entirely virtual, comprising the online resources, supported by 3 x zoom Q&A sessions.

Wednesday 7 May

10:00
Bayesian Statistics new (1 of 4) [Full] 10:00 - 12:00 CaRM pre-recorded lecture(s) on Moodle

The purpose of this course is to familiarise students with the basic concepts of Bayesian theory. It is designed to provide an introduction to the principles, methods, and applications of Bayesian statistics. Bayesian statistics offers a powerful framework for data analysis and inference, allowing for the incorporation of prior knowledge and uncertainty in a coherent and systematic manner.

Throughout this course, we will cover key concepts such as Bayes' theorem, prior and posterior distributions, likelihood functions, and the fundamental differences between Bayesian and frequentist approaches. You will learn to formulate and estimate statistical models, update beliefs using new data, and make informed decisions based on the posterior probabilities generated through Bayesian inference. By the end of this course, you will possess the necessary skills to perform Bayesian data analysis, interpret results, and apply Bayesian methods in various contexts.

14:00
Bayesian Statistics new (2 of 4) [Full] 14:00 - 16:00 CaRM Zoom

The purpose of this course is to familiarise students with the basic concepts of Bayesian theory. It is designed to provide an introduction to the principles, methods, and applications of Bayesian statistics. Bayesian statistics offers a powerful framework for data analysis and inference, allowing for the incorporation of prior knowledge and uncertainty in a coherent and systematic manner.

Throughout this course, we will cover key concepts such as Bayes' theorem, prior and posterior distributions, likelihood functions, and the fundamental differences between Bayesian and frequentist approaches. You will learn to formulate and estimate statistical models, update beliefs using new data, and make informed decisions based on the posterior probabilities generated through Bayesian inference. By the end of this course, you will possess the necessary skills to perform Bayesian data analysis, interpret results, and apply Bayesian methods in various contexts.

Tuesday 13 May

11:00
Doing Qualitative Interviews (ET) (3 of 3) [Places] 11:00 - 11:30 CaRM Zoom

Face-to-face interviews are used to collect a wide range of information in the social sciences. They are appropriate for the gathering of information on individual and institutional patterns of behaviour; complex histories or processes; identities and cultural meanings; routines that are not written down; and life-history events. Face-to-face interviews thus comprise an appropriate method to generate information on individual behaviour, the reasons for certain patterns of acting and talking, and the type of connection people have with each other.

The first session provides an overview of interviewing as a social research method, then focuses on the processes of organising and conducting qualitative interviews. The second session explores the ethics and practical constraints of interviews as a research method, particularly relevant when attempting to engage with marginalised or stigmatised communities. The third session focuses on organisation and analysis after interviews, including interpretation through coding and close reading.

In Easter Term, the course is entirely virtual, comprising the online resources, supported by 3 x zoom Q&A sessions.

Wednesday 14 May

10:00
Bayesian Statistics new (3 of 4) [Full] 10:00 - 12:00 CaRM pre-recorded lecture(s) on Moodle

The purpose of this course is to familiarise students with the basic concepts of Bayesian theory. It is designed to provide an introduction to the principles, methods, and applications of Bayesian statistics. Bayesian statistics offers a powerful framework for data analysis and inference, allowing for the incorporation of prior knowledge and uncertainty in a coherent and systematic manner.

Throughout this course, we will cover key concepts such as Bayes' theorem, prior and posterior distributions, likelihood functions, and the fundamental differences between Bayesian and frequentist approaches. You will learn to formulate and estimate statistical models, update beliefs using new data, and make informed decisions based on the posterior probabilities generated through Bayesian inference. By the end of this course, you will possess the necessary skills to perform Bayesian data analysis, interpret results, and apply Bayesian methods in various contexts.

14:00
Bayesian Statistics new (4 of 4) [Full] 14:00 - 16:00 CaRM Zoom

The purpose of this course is to familiarise students with the basic concepts of Bayesian theory. It is designed to provide an introduction to the principles, methods, and applications of Bayesian statistics. Bayesian statistics offers a powerful framework for data analysis and inference, allowing for the incorporation of prior knowledge and uncertainty in a coherent and systematic manner.

Throughout this course, we will cover key concepts such as Bayes' theorem, prior and posterior distributions, likelihood functions, and the fundamental differences between Bayesian and frequentist approaches. You will learn to formulate and estimate statistical models, update beliefs using new data, and make informed decisions based on the posterior probabilities generated through Bayesian inference. By the end of this course, you will possess the necessary skills to perform Bayesian data analysis, interpret results, and apply Bayesian methods in various contexts.