Leverhulme Professorship Visit: Quantitative Ethnography in the Age of Big Data
25 Jan 2024
MIE to welcome Professor David Williamson Shaffer, University of Wisconsin-Madison, with a series of engagement events in the week beginning Monday 26 February
In late-February, the Digital Technologies, Communication & Education (DTCE) and Education & Psychology (EP) research and scholarship groups in MIE will be co-hosting Professor David Williamson Shaffer, University of Wisconsin-Madison, as part of a Leverhulme International Professorship visit. David’s research on merging statistical and qualitative methods to construct fair models of complex and collaborative human activity is internationally recognised. He has authored more than 250 publications with over 100 co-authors, including How Computer Games Help Children Learn and Quantitative Ethnography (which introduced Epistemic Network Analysis).
During David’s visit w/c February 26th, several events are being arranged:
Leverhulme Lecture on Quantitative Ethnography: Human Science in the Age of Big Data
Wednesday, 28 February, 1pm - 2pm
EWB C5.1 – sign-up not required
David Williamson Shaffer looks at the transformation of the social sciences in the age of Big Data: how to resolve the dichotomy between qualitative and quantitative methods and go beyond simple “mixtures” of methods — and how this transformation makes it possible to build meaningful and fair analyses of data about learning, culture, and human experience.
Leverhulme Workshop on Epistemic Network Analysis
Thursday, 29 February, 10am-12.30pm
Alan Turing Building
As places are limited to 25 colleagues (inc PGRs), sign-up is recommended asap: https://www.eventbrite.co.uk/e/leverhulme-workshop-on-epistemic-network-analysis-tickets-791027493527
This hands-on workshop introduces participants to the principles of Quantitative Ethnography (QE), an approach to analysing Big Data that goes beyond the old dichotomy of qualitative and quantitative methods and simple mixtures of methods. The workshop focuses on Epistemic Network Analysis (ENA), a tool for modelling complex and collaborative thinking within a QE framework. ENA models how humans make meaning of events in the world using large- and small-scale datasets of many kinds, including logfiles, transcripts of structured and semi-structured interviews, simulations, chat, email, and social media. A laptop with web access is helpful, but not required.
DTCE Seminar: Understanding Learning in the World of AI
Friday, 1 March, 10am-12pm
Sam Alex_A115 – sign-up not required
ChatGPT and other new advances in AI have the potential to change work, education, and even what it means to “think” in the first place. In this workshop, Prof Shaffer looks at what AI is (and isn’t), its impact on what and how we learn, and how AI can change what it means to do research. This will be followed by informal group discussion, networking, etc.
Some colleagues may also be interested to meet with David 1-to-1 during his visit, in which case kindly email louis.major@manchester.ac.uk no later than Friday, 2 February to express an interest.
If you are interested in learning more about other events DTCE and EP are organising in 2024, you can sign up to our mailing lists by:
DTCE: Completing this form – https://forms.gle/so8PzvpGUTEVvXTh7
EP: Emailing Kelly Burgoyne (Kelly.Burgoyne@manchester.ac.uk) and/or Ola Demkowicz (ola.demkowicz@manchester.ac.uk)