Integrating MAXQDA’s AI Assist features into the qualitative analysis workflow (Online)
Key information
- Start date:
- 14 November 2024
- Attendance dates:
14 November 2024
- Time commitment:
- 09:30- 16:30 UK time
- Venue:
- Distance learning
- Contact details:
- Administrative Officer, Short Courses
- Email: daycourses@surrey.ac.uk
- Sarah L. Bulloch, PhD.
- Lecturer
- Email: Sarah.bulloch@surrey.ac.uk
Overview
MAXQDA is a powerful software for qualitative and mixed-methods analyses of text, audio, video, survey and social media data. Having integrated generative AI features, the software now offers new possibilities to researchers.
This one-day course provides an overview of MAXQDA’s functionality and explores the latest in MAXQDA’s AI Assist tools. We consider moments within a qualitative data analysis workflow at which a researcher might lean on these AI tools, and the implications of doing so.
The course explores what use of these tools might look like within research contexts, encouraging a method-sensitive approach to harnessing generative-AI technologies.
Using a critical lens to think through context-specific adoption of these new technologies, this course focuses on developing appropriate uses of tools to accomplish tasks, cautioning against both indiscriminate use of AI tools and complete abstention of their use.
The course combines discussion, demonstration and hands-on work, including:
- Contextual discussions – developmental, methodological and analytical principles
- Software Overview –interface, architecture, manual & automated tools
- Analytic Planning – ensuring analytic strategies drive the appropriate use of software tools
- Guided Instruction – step-by-step teaching in the operation of MAXQDA and the use of tools for analytic tasks
Participants will work on sample data and the whole group follows common tasks together and practices exercises individually. Work is structured to provide step-by-step support, including project set up, manual and AI-assisted coding and summarising, organising data to key characteristics and interrogating materials.
Please note: This is MAXQDA 2024 course, as this is the first version to contain the AI Assist functionality. Participants using version 2022 or 2020 are welcome to attend but the main part of the course will cover the functions available for MAXQDA version 2024. The software is the same on Mac and Windows platform. Participants can use the trial version of MAXQDA 2024 to follow the course if they do not yet have a licence.
Learning outcomes
By the end of the course participants will be able to:
- Understand the structure of MAXQDA and how it can be used throughout a research project.
- Navigate around the software and operate it to undertake analysis.
- Understand the importance of analytic planning in harnessing MAXQDA tools powerfully.
- Set-up a MAXQA project to reflect initial research design and change structures as a research project progresses.
- Identify MAXQDA tools that can be used to fulfil specific analytic tasks, including Documents, manually created and AI-suggested Codes, Variables, Memos, manual and AI-assisted Summaries and Interrogation tools.
Make informed decisions about where and when it may be appropriate to use AI Assist tools within the qualitative analysis workflow.
Course content
- Introduction to MAXQDA’s components
- Tips for data preparation, transcription, import and organisation
- Data exploration and familiarisation, including AI-assisted summaries and AI-assisted Chat with Documents.
- Coding strategies – inductive, deductive approaches; manual and automated approaches; including AI assisted coding.
- Organising materials to factual characteristics such as socio-demographics (variables) to facilitate interrogation.
- Use of writing and visualisation tools to reflect on data and processes
- Querying and outputting
Learning and teaching methods
- Presentations
- Demonstrations,
- Guided hands-on exercises,
- Independent hands-on work
Assessment
None
Course leader
![](/themes/custom/surrey/assets/dist/img/profile_default_150x150.jpg)
Dr Sarah Bulloch
Teaching Fellow
Reading list
There is no required pre-course reading. However, the following might be helpful resources with your further work with MAXQDA:
- Silver, C., & Lewins, A. (2014). Using software in qualitative research: A step-by-step guide (2nd ed.). Thousand Oaks, CA: Sage.
- Woolf, N. H., & Silver, C. (2018). Qualitative analysis with MAXQDA: The Five-Level QDA method. NY: Routledge.
Dr Sarah Bulloch has been using and teaching CAQDAS packages for many years and is an experienced researcher. She has undertaken quantitative, qualitative and mixed methods research using dedicated software and has worked in academic and applied settings.
Entry requirements
None
This course assumes participants have a broad understanding of qualitative and/or mixed methods methodologies, but assumes no prior knowledge about MAXQDA.
Recognition of prior learning
None
This course is delivered online using Zoom. In order to attend you will need a computer (Mac or Windows) that has access to the internet, and a microphone (inbuilt or external). We encourage participants to share their image using a webcam to foster dialogue and interaction, but this is not a requirement.
You will also need MAXQDA 2024 installed and working on your computer ahead of the session to get the most out of the workshop. If you do not currently have access to the software, details on how to access a 30 day free trial can be found here: https://www.maxqda.com/trial
Fees and funding
Price per person:
£98
UGPN student discount£130
Students (all non-UGPN)£138
UGPN staff discount£155
Education and charitable sector applicants£230
Government and commercial sector applicantsWhat these fees include
Handout of slides. Post course email with links to further resources.
Funding opportunities
Funding opportunities
Participants applying for a UGPN discount will need to use their University email address to be eligible.
- North Carolina (NC) State University: @ncsu.edu
- University of Sāo Paulo (USP): @usp.br
- University of Wollongong: @uow.edu.au
- University of Surrey: @surrey.ac.uk
All staff and students at any of the above institutions are now eligible for the UGPN discount as part of UGPN.
Terms and conditions
When you accept an offer of a place at the University of Surrey, you are agreeing to comply with our policies and regulations and our terms and conditions. You are also confirming you have read and understood the University's prospective student privacy notice.
Further details of our terms and conditions will follow.
Disclaimer
This online prospectus has been prepared and published in advance of the commencement of the course. The University of Surrey has used its reasonable efforts to ensure that the information is accurate at the time of publishing, but changes (for example to course content or additional costs) may occur given the interval between publishing and commencement of the course. It is therefore very important to check this website for any updates before you apply for a course with us. Read the full disclaimer.
Course location and contact details
Campus location
Stag HillStag Hill is the University's main campus and where the majority of our courses are taught.
- Email: daycourses@surrey.ac.uk
University of Surrey
Guildford
Surrey GU2 7XH