Cambridge Research Methods (CaRM) course timetable
Monday 10 February
10:00 |
This module aims to provide a practical guide to developing research projects using quantitative methods. It will focus on quantitative research design, key statistical concepts and methods, applied social statistics in education research and social policy evaluation. While the illustrative examples will mainly come from education and policy research, the knowledge and skills acquired through this module may also apply to other quantitative social sciences research projects. Outline The module consists of four lectures (two-hours per session) including:
Contents Lecture 1 will focus on how to design quantitative studies, including formulating research questions, engaging with theoretical and empirical evidence, developing hypothesises, as well as preparing relevant data. Lecture 2 will cover some of the widely used statistical toolkits for data description and hypothesis testing, such as z-score, conference intervals, parametric and non-parametric tests, correlation and regression analyses. Lecture 3 applies the principles of research design and key statistical methods to examples drawn from education research. It will highlight regression analyses and the interpretation of statistical outputs. Lecture 4 will introduce causal inference methods, such as instrumental variables, difference-in-differences and regression discontinuity design, which are commonly used in social policy evaluation. |
Doing Multivariate Analysis Using R (DMA 4)
Not bookable
This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself , and to interpret and write about your results intelligently. Half of the module is based on pre-recorded lectures that can be accessed via the Moodle page where you will be introduced to statistical theory, concepts, and techniques. Although these pre-recorded lectures will be available for you to access over the academic year, it is important that you watch the appropriate pre-recorded lectures before the start of each corresponding practical workshop. The other half of the module consists two in-person practical workshops. In these workshops you will have the opportunity to apply the newly learned methods and techniques of multivariate regression by working through practical exercises using the software R. During the workshops staff and demonstrators will be at hand to answer answer any questions or issues you may have. To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models. |
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Doing Multivariate Analysis Using Stata (DMA-5)
Not bookable
This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently. Half of the module is based on pre-recorded lectures that can be accessed via the Moodle page where you will be introduced to statistical theory, concepts, and techniques. Although these pre-recorded lectures will be available for you to access over the academic year, it is important that you watch the appropriate pre-recorded lectures before the start of each corresponding practical workshop. The other half of the module consists two in-person practical workshops. In these workshops you will have the opportunity to apply the newly learned methods and techniques of multivariate regression by working through practical exercises using the software Stata. During the workshops staff and demonstrators will be at hand to answer answer any questions or issues you may have. To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models. |
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14:00 |
Doing Multivariate Analysis Using R (DMA 4)
Not bookable
This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself , and to interpret and write about your results intelligently. Half of the module is based on pre-recorded lectures that can be accessed via the Moodle page where you will be introduced to statistical theory, concepts, and techniques. Although these pre-recorded lectures will be available for you to access over the academic year, it is important that you watch the appropriate pre-recorded lectures before the start of each corresponding practical workshop. The other half of the module consists two in-person practical workshops. In these workshops you will have the opportunity to apply the newly learned methods and techniques of multivariate regression by working through practical exercises using the software R. During the workshops staff and demonstrators will be at hand to answer answer any questions or issues you may have. To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models. |
16:00 |
Doing Multivariate Analysis Using Stata (DMA-5)
Not bookable
This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently. Half of the module is based on pre-recorded lectures that can be accessed via the Moodle page where you will be introduced to statistical theory, concepts, and techniques. Although these pre-recorded lectures will be available for you to access over the academic year, it is important that you watch the appropriate pre-recorded lectures before the start of each corresponding practical workshop. The other half of the module consists two in-person practical workshops. In these workshops you will have the opportunity to apply the newly learned methods and techniques of multivariate regression by working through practical exercises using the software Stata. During the workshops staff and demonstrators will be at hand to answer answer any questions or issues you may have. To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models. |
Tuesday 11 February
10:30 |
Doing Qualitative Interviews (LT)
In progress
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 Lent Term, the online resources are supported by 1 x zoom Q&A session, and 2 x in-person workshops. During the first in-person workshop students will role-play interviews using the scenarios outlined in the course moodle pages. During the second in-person workshop students will work in pairs on their interview material (at whatever stage of the process: whether writing interview questions, coding or analysing data) in order to receive advice and support in taking the interview material/data to the next stage of the research process. |
12:00 |
Causality in Statistics (LT)
![]() The module introduces causal inference methods that are commonly used in quantitative research, in particularly social policy evaluations. It covers the contexts and principles as well as applications of several specific methods - instrumental variable approach, regression discontinuity design, and difference-in-differences analysis. Key aspects of the module include investigations of the theoretical basis, statistical process, and illustrative examples drawn from research papers published on leading academic journals. The module incorporates both formal lecturing and lab practice to facilitate understanding and applications of the specific methods covered. The module is suitable for those who are interested in quantitative research and analysis of causality across a range of topics in social sciences. |
14:00 |
Public Policy Analysis
In progress
The analysis of policy depends on many disciplines and techniques and so is difficult for many researchers to access. This module provides a mixed perspective on policy analysis, taking both an academic and a practitioner perspective. This is because the same tools and techniques can be used in academic research on policy options and change as those used in practice in a policy environment. This course is provided as three 2-hour sessions. No direct analysis work will be done in the sessions themselves, but some sample data and questions will be provided for students who wish to take the material into practice. |
16:00 |
Have you received or collected your data (or anticipate doing so!), but are not sure what to do next? This course is designed to equip you with the skills you need to efficiently clean, reformat, and prepare your datasets using Stata. Ideal for social science researchers and analysts who want to use quantitative data for their dissertation or other research project and want to prepare their data efficiently and follow best practices. Over four interactive sessions, you will master essential techniques for handling missing data, merging and appending datasets, batch processing, and recoding variables. Each session combines concise, focused lectures with practical, hands-on exercises using either your own data or datasets provided by the instructor. |
Wednesday 12 February
10:00 |
Doing Multivariate Analysis Using R (DMA 4)
Not bookable
This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself , and to interpret and write about your results intelligently. Half of the module is based on pre-recorded lectures that can be accessed via the Moodle page where you will be introduced to statistical theory, concepts, and techniques. Although these pre-recorded lectures will be available for you to access over the academic year, it is important that you watch the appropriate pre-recorded lectures before the start of each corresponding practical workshop. The other half of the module consists two in-person practical workshops. In these workshops you will have the opportunity to apply the newly learned methods and techniques of multivariate regression by working through practical exercises using the software R. During the workshops staff and demonstrators will be at hand to answer answer any questions or issues you may have. To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models. |
Doing Multivariate Analysis Using Stata (DMA-5)
Not bookable
This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently. Half of the module is based on pre-recorded lectures that can be accessed via the Moodle page where you will be introduced to statistical theory, concepts, and techniques. Although these pre-recorded lectures will be available for you to access over the academic year, it is important that you watch the appropriate pre-recorded lectures before the start of each corresponding practical workshop. The other half of the module consists two in-person practical workshops. In these workshops you will have the opportunity to apply the newly learned methods and techniques of multivariate regression by working through practical exercises using the software Stata. During the workshops staff and demonstrators will be at hand to answer answer any questions or issues you may have. To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models. |
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This module will introduce the concept of planetary health and explore the importance of ensuring researchers recognise the wider determinants of climate change, biodiversity, and ecological best practices applied to research. The face to face workshop will offer presentations and opportunities to reflect on practical improvements that individuals and research groups might make to limit their carbon footprint and potentially enhance environments through their research. Discussion may include some of the barriers to local actions and therefore explore wider systems perspectives on how Universities are able to transform their activities in the light of climate breakdown and build resilience to environmental shocks. The tutors are committed to promoting ecocentrism with staff and students and hope to enable positive action towards net zero academic practices. |
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14:00 |
Doing Multivariate Analysis Using R (DMA 4)
Not bookable
This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself , and to interpret and write about your results intelligently. Half of the module is based on pre-recorded lectures that can be accessed via the Moodle page where you will be introduced to statistical theory, concepts, and techniques. Although these pre-recorded lectures will be available for you to access over the academic year, it is important that you watch the appropriate pre-recorded lectures before the start of each corresponding practical workshop. The other half of the module consists two in-person practical workshops. In these workshops you will have the opportunity to apply the newly learned methods and techniques of multivariate regression by working through practical exercises using the software R. During the workshops staff and demonstrators will be at hand to answer answer any questions or issues you may have. To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models. |
Feminist Research Practice
In progress
This series of workshops are aimed at students interested in interdisciplinary and feminist research practice. The course revolves around a simple query: what makes research feminist? It is the starting point to engage with classic and more contemporary writings on feminist knowledge production to answer some of the following questions: what are the ‘proper’ objects of feminist research? Who can do feminist research? Why do we do feminist research, and what is its relevance? Who do we cite in our research? We will have in-class discussions and hands-on assignments that will allow students to practice some of the main debates we will read about. |
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15:00 |
This course introduces students to discourse analysis with a particular focus on the (re)construction of discourse and meaning in textual data. It takes students through the different stages of conducting a discourse analysis in four practical-oriented sessions. The overall course focus is guided by a Foucauldian and Critical Discourse Analysis approach, conceptualising discourses as not only representing but actively producing the social world and examining its entanglement with power. The first session gives an overview of theoretical underpinnings, exploring the epistemological positions that inform different strands of discourse analysis. In the second session, we delve into the practical application of discourse analysis of textual data. Topics covered include, among others, what research questions and aims are suitable for discourse analysis as well as data sampling. In the third session, we discuss how to analyse textual data based on discourse analysis using the computer-assisted qualitative data analysis software Atlas.ti. The fourth session will take a workshop format in which students apply the gained knowledge by developing their own research design based on discourse analysis. |
16:00 |
Doing Multivariate Analysis Using Stata (DMA-5)
Not bookable
This module will introduce you to the theory and practice of multivariate analysis, covering Ordinary Least Squares (OLS) and logistic regressions. You will learn how to read published results critically, to do simple multivariate modelling yourself, and to interpret and write about your results intelligently. Half of the module is based on pre-recorded lectures that can be accessed via the Moodle page where you will be introduced to statistical theory, concepts, and techniques. Although these pre-recorded lectures will be available for you to access over the academic year, it is important that you watch the appropriate pre-recorded lectures before the start of each corresponding practical workshop. The other half of the module consists two in-person practical workshops. In these workshops you will have the opportunity to apply the newly learned methods and techniques of multivariate regression by working through practical exercises using the software Stata. During the workshops staff and demonstrators will be at hand to answer answer any questions or issues you may have. To get the most out of the course, you should also expect to spend some time between sessions having fun by building your own statistical models. |
17:00 |
Ethics and the associated process of approval / review are an important component of any research project, not only practically enabling research to take place but also enabling researchers to consider the values underpinning their research. The aim of this course is to take both a practical and reflective approach to ethics. On a practical level, the course will focus on identifying the steps involved in seeking ethical approval or undertaking an ethical review. On a reflective level, the course will explore the values informing key ethical principles and concepts and how these may relate to individual’s research. |
Thursday 13 February
10:00 |
Evaluation Methods
[Places]
This course aims to provide students with a range of specific technical skills that will enable them to undertake impact evaluation of policy. Too often policy is implemented but not fully evaluated. Without evaluation we cannot then tell what the short or longer term impact of a particular policy has been. On this course, students will learn the skills needed to evaluate particular policies and will have the opportunity to do some hands on data manipulation. A particular feature of this course is that it provides these skills in a real world context of policy evaluation. It also focuses primarily not on experimental evaluation (Random Control Trials) but rather quasi-experimental methodologies that can be used where an experiment is not desirable or feasible. |
Qualitative Data Analysis with Atlas.ti
In progress
This course provides an introduction to the management and analysis of qualitative data using Atlas.ti. It is divided between mini-lectures, in which you’ll learn the relevant strategies and techniques, and hands-on live practical sessions, in which you will learn how to analyse qualitative data using the software. The sessions will introduce participants to the following:
Please note: Atlas.ti for Mac will not be covered. |
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12:00 |
Causality in Statistics (LT)
![]() The module introduces causal inference methods that are commonly used in quantitative research, in particularly social policy evaluations. It covers the contexts and principles as well as applications of several specific methods - instrumental variable approach, regression discontinuity design, and difference-in-differences analysis. Key aspects of the module include investigations of the theoretical basis, statistical process, and illustrative examples drawn from research papers published on leading academic journals. The module incorporates both formal lecturing and lab practice to facilitate understanding and applications of the specific methods covered. The module is suitable for those who are interested in quantitative research and analysis of causality across a range of topics in social sciences. |
14:00 |
Evaluation Methods
[Places]
This course aims to provide students with a range of specific technical skills that will enable them to undertake impact evaluation of policy. Too often policy is implemented but not fully evaluated. Without evaluation we cannot then tell what the short or longer term impact of a particular policy has been. On this course, students will learn the skills needed to evaluate particular policies and will have the opportunity to do some hands on data manipulation. A particular feature of this course is that it provides these skills in a real world context of policy evaluation. It also focuses primarily not on experimental evaluation (Random Control Trials) but rather quasi-experimental methodologies that can be used where an experiment is not desirable or feasible. |
15:30 |
Ethnographic Methods
In progress
This module is an introduction to ethnographic fieldwork and analysis, as these are practiced and understood by anthropologists. The module is intended for students in fields other than anthropology.
Session overview Session 1: The Ethnographic Method
Session 2: Digital Ethnography Part I In these sessions, we discuss anthropologically-informed ethnographic practices of "the digital." In the first session we define what is meant by "digital" and delineate the various ways in which the digital presents itself in everyday life, in order to ascertain the appropriate ethnographic methods for each. The first session explores theoretical conversations and research ethics before moving on to discuss the implications of digital mediations on people's lives and on ethnographic practice, including reconsiderations of what online and offline behavior represents. What are some similarities, differences, connections, and disconnections between ‘online’ and ‘offline’ forms of interaction, sociality, and social norms? Do people act in the same ways in ‘online’ versus ‘offline’ spaces? Is even such a distinction valuable? A case study will be provided to consider these issues. Session 3: Digital Ethnography Part II In the second session we will focus on digital technologies as 'tools' in facilitating and/or complementing ethnographic fieldwork. We will look at various case studies (provided in the reading list; participants are asked to read at least one beforehand) in order to assess the advantages and potential limits of digital technologies such as mobile/smart phones, geospatial tracking/mapping technologies, recording and data storage technologies, software for organizing and analyzing field data, and the mining of ‘big data’ sets. Session 4: Youth-centred and Symmetric Classroom Ethnography This session provides an introduction to ethnographic research methods with a particular focus on working with young interlocutors. While grounded in social anthropology, it is designed to be accessible to students across the social sciences. We will explore the distinctive challenges and opportunities of researching youth and youth cultures, especially within educational settings. Recognizing the varying demands of different research contexts, we will discuss approaches to conducting both immersive and shorter-term, youth-centered ethnographies, inside and outside the classroom. Emphasis will be placed on the principles of symmetry and reciprocity in the researcher-participant relationship. The session will open with a theoretical overview of key themes, followed by an analysis of a case study drawn from long-term anthropological research within a multicultural educational environment, also highlighting the evolving youth cultures within such a milieu. The latter part of the session will involve interactive activities designed to equip students with practical tools for applying ethnographic methods in their own research projects. Session 5: Multimodal Youth-led Citizen Social Science In this session students will be introduced to 'multimodal' thinking and doing in fieldwork (multimodal literally means 'the different ways in which something occurs or is experienced'). We will practically unpack some of the ways of crafting what are known as 'fieldnotes', which are most commonly done via text but which can take a number of different forms. We will also think about how the varied approaches anthropologists take to document what they meet in their fieldsites can significantly impact the shaping of their subsequent analysis. We will unpack the pros and cons of different techniques of documentation including: text, drawing, sound recording, filmic capture, and photovoice. |
16:00 |
Reading and Understanding Statistics (LT)
In progress
This module is for students who don’t plan to use quantitative methods in their own research, but who need to be able to read and understand published research using quantitative methods. You will learn how to interpret graphs, frequency tables and multivariate regression results, and to ask intelligent questions about sampling, methods and statistical inference. The module is aimed at complete beginners, with no prior knowledge of statistics or quantitative methods. |
Have you received or collected your data (or anticipate doing so!), but are not sure what to do next? This course is designed to equip you with the skills you need to efficiently clean, reformat, and prepare your datasets using Stata. Ideal for social science researchers and analysts who want to use quantitative data for their dissertation or other research project and want to prepare their data efficiently and follow best practices. Over four interactive sessions, you will master essential techniques for handling missing data, merging and appending datasets, batch processing, and recoding variables. Each session combines concise, focused lectures with practical, hands-on exercises using either your own data or datasets provided by the instructor. |
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17:00 |
Semiotic and Cultural Semantic Analysis
![]() The module aims to provide students with an introduction to semiotics and cultural semantics. It will overview semiotic and cultural sematic approaches to cultural, literary, and social studies. The focus is on key aspects of semiotics and cultural semantics, including their key concepts and usage in research design and objectives. The module will explore the differences between approaches as opposed perspectives on cultural symbolism. While illustrative examples are mainly drawn from cultural, visual, and literary research, the skills acquired through this module are also applicable to other topics and areas in the social sciences. Outline The module is structured into two lectures and two workshops, each lasting two hours:
Contents Lecture 1 will cover a brief overview of semiotics and cultural semantics, introducing key terms and distinctions between semiotic and semantic approaches to cultural studies. It will address strategies for investigating cultural symbolism and the meaning-making process. Lecture 2 will delve into widely used concepts in both fields, such as cultural meaning, cultural text, symbol, sign, elementary communication structure and sign structure. This focus is on understanding cultural semiosis, symbolisation, and the meaning-making process. The lecture will explore both approaches in discussing cultural values, meanings, texts, and artifacts. Workshop 3 will teach students how to reconstruct cultural code as a key structure for understanding cultural symbolisation. It will include the practical examples of reconstructing the cultural code related to single motherhood through literary texts. Workshop 4 will introduce recent studies in visual grammar, drawing on surveys in children’s picturebooks. This session aims to explore the application of social semiotics in visual studies, emphasizing the analysis of visual elements in cultural symbolism and meaning making. |
17:30 |
Open Source Investigation for Academics (LT)
In progress
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. |