Cambridge Research Methods (CaRM) course timetable

Web scraping has great potential as a research tool that can be applied across various fields of research including social science and humanities, and allows us to reach beyond the ‘quantitative and qualitative divide’. The programming and code-reading/analysing skills used in web scraping can enhance our understanding of digital power beyond the traditional limits of computing techniques.

This two-hour training module (plus 1-hour online Q&A session) introduces researchers to how to use Python software for web scraping. You will learn what web scraping means, the principles behind it, and ethical considerations, and importantly how to use Python to achieve web scraping. The module provides a good opportunity to learn how to enhance your coding and code-reading skills, from which you can reflect on how digital power especially web scraping and coding is shaping contemporary research. The training is programming beginner friendly.

For the 1hr online Q&A session the first 30mins are used for extend web scraping with other tools including R, followed by Q&A tutorials. Please ensure you have basic knowledge in using R if you would like to join the first 30mins, but the Q&A are available to all the students.

This module introduces observation as a research method. Attention is given to the key elements and methodological consideration of conducting observations. It also explores the process of conducting observation, where students are given the opportunity to experiments elements of observation, and to experience the role of researcher in the practical workshop. There is also an online clinic session where students are given one-to-one opportunities to ask questions at the end of the course. This course is especially suitable for those who consider using observation as a research method within educational contexts.

This course will provide a detailed critique of the methods and philosophy of the Null Hypothesis Significance Testing (NHST) approach to statistics which is currently dominant in social and biomedical science. We will contrast NHST with alternatives, especially with Bayesian methods. We will use computer code to demonstrate some issues. However, we will focus on the big picture rather on the implementation of specific procedures.

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).

In this two-part course we will introduce students to the concepts of policy analysis and impact evaluation. In doing so we first cover some definitions, what policy impacts or processes are we attempting to measure? We then focus on different ways to measure the impacts of a policy including ex-ante and ex-post methods. On Day 1 we focus on ex-post analysis (i.e., examining what happened after the policy has already been implemented). We focus on the concept and measurement of additionality and spillovers, and then zoom in on types of quantitative econometric methods, as well as qualitative processes tracing approaches. On Day 2 we focus on ex-ante analysis (i.e. examining what may happen if a policy is adopted and implemented). We describe quantitative and qualitative methods that can be used to evaluate potential impacts, including scenario modelling, Delphi analysis, and realist evaluation.

Please note that, on Tuesday 11 March, the first part of Session 1 (09:30-12:30) will take place in Titan Teaching Room 3 in the Cockcroft Building on the New Museums site. After the lunch break, the session will move to the Large Lecture theatre in the main Geography building (13:30-15:30).

This module is centred around identifying biases from the start of research design, through to final write-up; establishing one's epistemological position in assessing research problems and conducting analysis, including assumption of findings.

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.

This module introduces drawing as a research method, with a particular focus on the key elements and methodological considerations for using drawing as a visual research method, and the pairing of drawing with qualitative interviews. This module explores examples of using drawing as a research method across disciplines, and students are offered hands-on experience to practice using drawing as a research method through a practical workshop. There is also an online clinic session where students are given one-to-one opportunities to ask questions at the end of the course.

Open Source Investigation for Academics is methodology course run by Cambridge’s Digital Verification Corps, in partnership with Cambridge’s Centre of Governance and Human Rights, Cambridge Research Methods and Cambridge Digital Humanities, as well as with the Citizen Evidence Lab at Amnesty International.

Please note that places on this module are extremely limited, so please only make a booking if you are able to attend all of the sessions.

Want to use secondary data but don’t know where to start? Have a research question in mind but don’t know how to go about finding a suitable dataset?

Using secondary data (that is, data collected by someone else, usually a government agency or large research organisation) has a number of advantages in social science research: sample sizes are usually larger than can be achieved by primary data collection, samples are more nearly representative of the populations they are drawn from, and using secondary data for a research project often represents significant savings in time and money. This short module, taught by Dr Deborah Wiltshire of the UK Data Archive, is an introductory course for students who have little or no prior training in working with survey data or statistical analysis. The module will focus on getting started with secondary data and, using longitudinal data, we will cover the following topics:

• What is secondary data & how can we use it?

• How to search for secondary data via data archives and search engines

• How to access secondary data

• Exploring and understanding data using the UK Household Longitudinal Study data

Using secondary data (that is, data collected by someone else, usually a government agency or large research organisation) has a number of advantages in social science research: sample sizes are usually larger than can be achieved by primary data collection, samples are more nearly representative of the populations they are drawn from, and using secondary data for a research project often represents significant savings in time and money.

This is an introductory module for students who have little or no prior training in working with survey data or statistical analysis. In this course we will focus on cleaning and preparing your data ready for analysis, using longitudinal data as an example. We will then start exploring how to produce and report descriptive statistics and regression analyses using Stata.

This module introduces observation as a research method. Attention is given to the key elements and methodological consideration of conducting observations. It also explores the process of conducting observation, where students are given the opportunity to experiments elements of observation, and to experience the role of researcher in the practical workshop. There is also an online clinic session where students are given one-to-one opportunities to ask questions at the end of the course. This course is especially suitable for those who consider using observation as a research method within educational contexts.

This is the first 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 sepaarately.

Workshop 1: Research design and the impact of (de)coloniality on our research projects

In this session we’ll place our disciplines in the historic context of their emergence and ask what implications this historicization has on our research in the present. We’ll then discuss a number of scholars who propose decoloniality and/or decolonisation as theoretical frames through which we can approach our research. In terms of practical skills, we’ll look to the emerging field of citational justice, asking how who and what we cite impacts the work we produce. We’ll also examine our research questions and explore their potential contributions to the reproduction of or resistance to deeper structures of power.

This module introduces drawing as a research method, with a particular focus on the key elements and methodological considerations for using drawing as a visual research method, and the pairing of drawing with qualitative interviews. This module explores examples of using drawing as a research method across disciplines, and students are offered hands-on experience to practice using drawing as a research method through a practical workshop. There is also an online clinic session where students are given one-to-one opportunities to ask questions at the end of the course.

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.

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.

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).

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.