Instructor: Nils Holmberg, Lund University, Department of Strategic Communication
Dates: 16–20 September (week 38), 9:00–12:00
Click here for the schedule and location info (the schedule and location is currently not finalised, the link will be updated)

Abstract: In this introduction to Python for social scientists you will learn how to use the Python programming language as a unified platform for handling multiple tasks and workflows connected to running research studies, collecting data, and analysing numeric and textual data. On the first day we will get familiarised with the Python command prompt, writing basic control structures, and utilising the scipy stack (numpy, pandas, etc). On the second day, we will practice building an online survey experiment using psychopy package and collect data. The third day will be dedicated to performing basic statistics, data analysis and visualisation within the seaborn package. On day four, we will use the spaCy package powered by machine learning libraries for various natural language processing applications. On the fifth and final day, we will learn how to use the jupyter notebooks and google colab for sharing and collaborating on Python code.

About the instructor

Nils Holmberg has a doctoral degree in Media and Communication Science from Lund University in December 2016. The focus of his dissertation was to investigate the effects of web advertising on children aged 9-12 when they use the internet to solve different types of tasks, e.g. read and understand texts in an online newspaper. To investigate this, he used experimental methods to systematically vary the content and form of web ads. Physiological measuring equipment was then used to investigate how different advertising properties affected children's visual attention and ability to solve tasks online. He has used Python extensively over the years to collect and analyse data.

Instructor: Tullia Jack, Lund University, Department of Service Studies
Dates: 24–25 September (week 39), 9:00-12:00
Click here for the schedule and location info (the schedule and location is currently not finalised, the link will be updated)

Abstract: Can we use artificial intelligence (AI) to code qualitative data? Can ChatGPT help detect themes? How can we use language models to brainstorm analysis avenues? Will it be possible for Chat tools to conduct interviews? In this workshop we explore these questions, using AI in qualitative data analysis in hands-on format. We will test a variety of AI-powered text analysis tools and platforms that can assist with data coding, theme extraction, sentiment analysis, text summarization and more. Bring your curiosity and laptop - no experience with AI necessary.
Learning outcomes
•    Train AI in your qualitative data.
•    Use AI to find themes.
•    Use AI for deductive coding.
•    Using AI to brinstorm.
•    Understand ethical considerations and best practices when using AI, including issues related to privacy, bias, and transparency.
•    An increased curiosity and confidence in engaging AI to analyse qualitative data.

Prerequisites:
No prior experience with AI is required. Participants should have a basic understanding of research methods and an interest in exploring the potential of AI in qualitative analysis.

About the instructor

Tullia Jack is an Associate Senior Lecturer at the Department of Service Studies at Lund University in Helsingborg. She is also a Marie Skadodowska-Curie International Fellow researching the consumption impact of living alone at Aalborg University in Copenhagen.
Her main research and teaching areas are Sustainability, Social practices, and Consumption. She is currently investigating why cleanliness expectations are increasing despite our raising awareness of the imperative to save water and energy. She uses domestic water and energy consumption, time use surveys, observations, and interviews for her research. She is involved in teaching subjects including Research Methods, Sustainable Fashion, and Managing Sustainability, Society, and Collective Behaviour. Her research interests are in sustainability, consumption, and everyday life.

Instructor: Christopher Swader, Lund University, Department of Sociology
Dates: 30 September–4 October (week 40), 9:00–12:00
Click here for the schedule and location info (the schedule and location is currently not finalised, the link will be updated)

Abstract: The workshop provides an introduction to the R programming language for the purpose of data analysis in the social sciences. R is an increasingly popular scientific tool and often becomes the first-choice software for implementing newly developed statistical and computational methods, especially within academia. The main goal of the workshop is that participants learn the basic functionality of R language that covers the full cycle of data analysis including data loading, pre-processing, visualisation, modelling, and communication of the results. The practical work is based on real data problems and prepares participants for a whole range of diverse data analysis tasks.

About the instructor

Christopher Swader is an Associate Professor (Docent/Senior Lecturer) at the Department of Sociology in Lund. His previous academic appointments were with the Higher School of Economics in Moscow (prior to 2015) and the University of Bremen in Germany. His work focuses on the connection between intimacy, modernisation, and normative order, which he has approached through multiple and mixed methods. He serves as the founding Programme Director of the Social Scientific Data Analysis master programme at LU's Graduate School. He has developed a model machine learning method ('ICRegress'), visualisations, and robustness routines, available on GitHub (https://github.com/ChristopherSwader), in addition to numerous innovation projects, each implemented using the R programming language.

Instructor: Benjamin Claréus, Lund University, Department of Psychology
Dates: September 30-4 October (week 40), 13:00-16:00
Click here for the schedule and location info (the schedule and location is currently not finalised, the link will be updated)

Abstract: NVivo is a Computer-Assisted Qualitative Data Analysis Software (CAQDAS) with the potential of facilitating qualitative analysis, mixed methods research, and literature synthesis/review. It can be used to compile data from fieldwork, interviews, images, research articles and more, and to create and organise codes and notes during the analytic process.
During this workshop, we will discuss how CAQDAS in general and NVivo in particular can and can’t support our analytic endeavours, and familiarise ourselves with some of NVivo’s basic (e.g., node creation and merging) and more advanced functions (e.g., matrix coding). 
Participants are encouraged to bring their own empirical material to work on during the workshop. No prior knowledge of NVivo or qualitative methods is required.

About the instructor

Benjamin Claréus is a PhD in Psychology and has been teaching research methods at the Faculty of Social Sciences for the past few years. He has applied NVivo in his own research, for example, in conducting narrative analysis and in synthesising literature for his dissertation.

Instructors: 
Jessica Daikeler, Leibniz Institute for the Social Sciences, Survey Design and Methodology
Dates: 3-4 October (week 40), 13:00-16:00
Click here for the schedule and location info (the schedule and location is currently not finalised, the link will be updated)

Abstract: The increasing amount of literature in many social science fields makes it difficult for resarchers to assess and keep up with new evidence. As a result, systematic reviews and meta-analyses play an important role in synthesising research and help researchers and practitioners make evidence-based decisions. The aim of this two-day course is to provide participants with an applied introduction to methods for conducting systematic reviews and meta-analyses in the social sciences also in the light of new AI-based tools. The course focuses on all parts of a research synthesis, from how to formulate a research question, search and evaluate the literature, extract and code the data and finally, integrate findings using meta-analytic models. The course will be interactive and practical. There will be opportunities to get individual consultation on your own research ideas. Prior use of R is advantageous.

About the instructors

Dr. Jessica Daikeler is a PostDoc at GESIS Leibniz Institute for the Social Sciences 
in the Survey Design and Methodology (SDM) department. She has worked on the application of evidence-based methods in the Social Sciences, such as experiments, systematic reviews and meta-analyses, supervised the GESIS Survey Guidelines and developed the GESIS Survey Methods Evidence Map. Her research interests are in empirical social research, survey research, application of evidence-based research methods, and research on and with digital behavioural data. 

Instructor: Helle Rydström, Lund University, Department of Gender Studies
Dates: 7-8 October (week 41), 9:00-12:00
Click here for the schedule and location info (the schedule and location is currently not finalised, the link will be updated)

Abstract: Ethnographic method has gained traction in the social sciences and has become an integrated component of virtually all social science disciplines. Yet, it is often opaque what is meant by ethnography, an ethnographic method, and ethnographic fieldwork.

This workshop critically considers ethnography as a method, as a practice, and as an analytical tool. The workshop aism at first; re-conceptualising the epistemologies and ontologies of ethnographic fieldwork, and second; processing ethnographic data gathered by the aid of various in-depth techniques such as observations, interviews, narratives, memories, testimonies, focus group discussions, questionnaires, and archive material.

Drawing on participants' fieldwork experiences, plans, and findings, the workshop will explore:

1. Preparing ethnographic fieldwork.
2. Collecting ethographic data.
3. Analysing ethnographic material.
4. Translating ethnographic findings into text.

Whether ethnographic fieldwork is conducted on the ground or virtually, questions are generated in connection with the researcher 'going there', 'being there', 'leaving' and 'returning'. These issues will be addressed at the workshop by examining ethnographic knowledge production, representation, and ethics as well as experiences, encounters, and emotions.

The workshop unfolds ethnographic fieldwork against the backdrop of decolonial and postcolonial scholarship and debates to understand the socio-political aspects of ethnography in a global world and how parameters such as gender, age, class, ethnicity, and sexuality inform ethnographic practices. In doing so, the workshop critically reflects upon the challenges which ethnographic fieldwork might impose upon those involved; whether it is an intrusive way of collecting data; could be carried out collaboratively; and whether ethnogrpahic fieldwork could be an act of solidarity.

About the instructor

Helle Rydström is Professor at the Department of Gender Studies at Lund University, Sweden. She has a background in Social Anthropology and International Development Studies as well as Interdisciplinary Studies (child/youth research with anthropology focus) and East and Southeast Asian Studies. Rydström is specialised in the anthropology of gender in Asia with a focus on Vietnam.

Her research covers various topics to explore the entanglements of crisis, precariousness, and harm, and the ways in which resilience is mustered and coping strategies invented. Thus, she has published on gendered hierarchies, powers, (in)securities, and violences as informed by ideas about masculinities, femininities, and sexualities to unfold how these shape lifeworlds and livelihoods including in the aftermath of climate disasters, colonialism, conflicts, and wars.

Instructor: Jean-Christophe Rohner, Lund University, Department of Psychology
Dates: 7-11 October (week 41), 9:15-12:00

Click here for the schedule and location info (the schedule and location is currently not finalised, the link will be updated)

Abstract: First order logic (FOL) is a highly expressive formal language with the capacity to accurately represent even complex theories, assumptions, and observations. FOL also supports deduction, induction, and abduction, three fundamental kinds of scientific inference, by defining them formally and by enabling the use of computer algorithms for inference. The implication is that researchers can use FOL to describe and reason about social-science phenomena at the individual level, group level and society level, e.g. thoughts, emotions, behaviors, group constellations, social structures, norms.
The workshop consists five sessions, where participants learn how to use the Prolog language (a type of FOL) for knowledge representation and inference. Each session involves a theoretical part plus a practical segment with hands on guidance from the facilitator. These have the following content. 

1. Scientific languages, syntax and semantics of logic programs.
2. Encoding theories in logic programs.
3. Deduction: Drawing conclusions.
4. Abduction: Finding explanations.
5. Induction: Generalising observations to theories.

About the instructor: 

Jean-Christophe got a doctoral degree in psychology in 2002; the topic of his dissertation was attention mechanisms in anxiety. Since then he has done research in social psychology, memory, and quantitative measurement models, and, more recently, the use of first order logic in science.

Instructor: Karen Waltorp, University of Copenhagen, Department of Anthropology
Dates: 9–10 October (week 41), 13:15–16:00

Click here for the schedule and location info (the schedule and location is currently not finalised, the link will be updated)

The focus in this course is on how to pay attention better, drawing from theoretical and methodological approaches to sensory ethnograhy and multimodal practice. Beginning with a general discussion of what sensory and multimodal ethnography is, and what these approaches afford researchers in terms of generating knowledge in various registers, the course introduces different ways of doing sensory ethnography and performing multimodal analysis, touching briefly on the dissemination/circulation of this knowledge. Particpants will discuss readings, and their own practice as it relates to these sets of methods and approaches, and have the opportunity to get hands-on experience with doing sensory ethnography and performing multimodal sorting and analysis. The course is for Ph.d.-students and researchers that work with ethnographic methods and/or are interested in learning more about sensory ethnography and multimodal practice. 

About the instructor:
Karen Waltorp is associate professor, filmmaker, and Head of the Ethnographic Exploratory and Multimodal MediaLab at the Department of Anthropology, University of Copenhagen. She has published widely on gender and minorities, emerging technologies and digital media ecologies, energy, and visual and multimodal anthropology. She is the author of Why Muslim Women and Smartphones: Mirror Images (Routledge 2020), co-editor of Energy Futures (DeGruyter 2022) and An Anthroology of Futues and Technologies (Routledge 2023), and has produced award-winning outputs in formats such as film, exhibition, and web. Waltorp is PI of DFC-funded CLAIMS to Energy Citizenship in South Africa (2024-2028), Danish Research Council-funded DigiSAt: Digital Everyday Lives far from Silicon Valley (2021-2024), and was Co-PI of AUFF-NOVA funded ARTlife (2017-2020), with the Afghan/Danish Film Collective ARTlife which emerged from the project still active, and selected for CPH Dox:Lab 2022-2023. She is member of editorial boards, incl. Cultural Anthropology and Visual Anthropology, and convenes the Multimodal Ethnography Network under the European Association of Social Anthropologists. 

Our Skill School workshops are primarily for teaching/research staff and doctoral students.

Students who sign up will only get a spot in the workshops that they want to attend in case there are openings. This only applies to students admitted to a master program at Lund University. If you are enrolled in Bachelor level studies or study at another institution, we will disregard your application.

All Skill School workshops are free-of-charge for all doctoral students at Lund University, as well as for all LU Faculty of Social Sciences staff.

For other cases, please sign up with your interest, and we will provide you with fee information for the workshops you are interested in attending. Alternatively, please send us an email at skillschool [at] sam [dot] lu [dot] se.

All the workshops will take place on campus in Lund, and it will not be possible to participate remotely. Detailed schedule and room information can be found under each relevant workshop listed above. If you are not familiar with the Paradise Campus where the majority of departments at the Faculty of Social Sciences are located, see this map.

Note that if you sign up for a workshop, but cannot attend, you must inform us two weeks before the workshop starts. Otherwise, your institution will be charged a no-show fee of 800 SEK for the missed workshop.

Our workshops are not designed as credit-bearing courses with officially established syllabi. However, you can ask your department/institution if you can earn credits if you submit a certificate of attendance with the description of the workshop (see next question about certificates of attendance).

Certificates for attending a workshop can be provided upon request from skillschool [at] sam [dot] lu [dot] se. Please note that you need to have attended 80% of the workshop to receive a certificate.

While some of our Skill School workshops are offered every year, we cannot guarantee that we will offer a certain workshop again in the future. Please check this page next spring for more information.