This podcast is part of the graduate level EdPsych 551: Quantitative Ethnography course in the MS in Educational Psychology - Learning Analytics program at University of Wisconsin-Madison. Each podcast episode features the program's faculty director, David Williamson Shaffer, conducting an interview with a scholar in the QE community about how they apply QE in their work as well as how they think about the methodology. Often Dr. Shaffer will reference a paper or talk written by the authors.
Interested in the Learning Analytics program?
Check out: www.learninganalytics.education.wisc.edu
Clare Porter is a recent graduate from University of Wisconsin – Madison where she was a senior research intern at the Epistemic Analytics lab and president of the Women in Economics student organization. She begins a position at the Rand Corporation in summer of 2022. In this conversation, Clare and Dr. David Williamson Shaffer discuss a behind-the-scenes look at the imperfect and iterative processes of QE research, as well as provide an introduction to how imperfect models are still a useful - and often essential - part of meaningful analytics.
Paper referenced:
Hansen, Zaki, Benna, Porter (2020). Epistemic Network Analysis of Reddit Comments Relating to COVID-19 Vaccine News on the r/Coronavirus Subreddit. In Wasson, B. & Zörgő, S. (eds.), Third International Conference on Quantitative Ethnography: Conference Proceedings Supplement.
18 Jun 2022
Week 2: Keeping the ‘E’ in QE with Adam Lefstein
Adam Leftstein (http://www.dialogicpedagogy.com/) is the Shane Family Professor of Education at the Ben-Gurion University of the Negev (https://in.bgu.ac.il/humsos/edu/rppedagogy/Pages/default.aspx) in Israel, and will be moving to Hebrew University in fall 2022 as Chair of the School of Education. He primarily uses linguistic ethnographic concepts and methods to study pedagogy, classroom interaction, teacher learning, change, and the movement of ideas between research and professional practice. In this episode, Adam and David discuss how to keep ethnography at the forefront when engaging in QE methods.
Talk referenced: ICQE ‘21 Keynote: https://www.youtube.com/watch?v=PD2G_2iNs7s (https://www.youtube.com/watch?v=PD2G_2iNs7s)
18 Jun 2022
Week 3: A Deep Dive into Segmentation with Szilvia Zörgő
Szilvia Zörgő is a cultural anthropologist by trade and has a PhD in mental health sciences. She is interested in qualitative, mixed, and unified research methods related to healthcare and information consumption, and is currently a Marie-Curie Fellow (//www.smart-searching.eu). In this episode, David and Szilvi talk about the nuances in how they segment their data and the effects segmentation decisions can have on the analysis.
18 Jun 2022
Week 4: Valid and Reliable with Danielle Espino & Seung Lee
Dr. Danielle Espino is a co-principal investigator and project manager at Pepperdine University for NSF-funded research examining cross-boundary collaboration in informal STEM learning (NSF Awards #1612824, #1824924), utilizing quantitative ethnography (QE) as a primary methodological approach on studies involving cross-cultural community building, global competences, connections between affect and discourse, group dynamics and advancing conversations on justice, equity, diversity and inclusion (JEDI).
Dr. Seung B. Lee is an Assistant Professor of Education at Pepperdine University in the Graduate School of Education and Psychology. His research focuses on collaborative learning, online interactions, socio-cognitive processes and creativity among K-12 students, particularly in the context of STEM education. He served as the Program Committee Co-chair for the 2020 International Conference on Quantitative Ethnography (ICQE).
In this joint conversation, Danielle and Seung talk about how they function as a team and discuss their collaborative efforts when working with QE.
18 Jun 2022
Week 5: Closing the Loop with Golnaz Arastoopour Irgens
Dr. Golnaz Arastoopour Irgens is an Assistant Professor of Learning Sciences (https://www.clemson.edu/education/about/directory/profile.html?userid=GARASTO) and the Director of the Inclusive Digital Education and Analytics (IDEA) Lab (//idealabclemson.org) at Clemson University. In her learning analytics work, she uses quantitative ethnography, computational linguistics, and discourse networks to make sense of how learners engage with digital technologies. In this episode, David and Gol discuss the iterative process of QE and why ‘closing the interpretive loop’ is a challenging but pivotal step in conducting a sound analysis.
Paper referenced:
Arastoopour Irgens, G. (2019). Facilitating a sense of belonging for women of color in engineering. In R. D. Roscoe, E. K. Chiou, & A. R. Wooldridge (Eds.), Advancing diversity, inclusion, and social justice through human systems engineering (pp. 221–239). CRC Press.
18 Jun 2022
Week 6: Weaving the Web with Zach Swiecki
Dr. Zachari Swiecki (https://research.monash.edu/en/persons/zachari-swiecki) is a Lecturer of Learning Analytics in the Faculty of Information Technology at Monash University. He received his master's and Ph.D. in Educational Psychology from the University of Wisconsin-Madison where he was a member of the Epistemic Analytics lab. Zach and David’s conversation offers background and framing for understanding QE processes.
Paper referenced:
Swiecki, Z., Lian, Z., Ruis, A., & Shaffer, D. W. (2019). Does order matter? investigating sequential and cotemporal models of collaboration.
18 Jun 2022
Week 7: Finding Your People with Yotam Hod
Yotam Hod (https://sites.google.com/view/dryotamhod/research) is currently an Associate Professor with the University of Haifa’s Faculty of Education. He is Head of the Educational Technologies Graduate Program (https://edtech.haifa.ac.il), Director of the LINKS Future Learning Spaces, was a Marie Curie Fellow (2018-2020) studying students' identities as knowledge builders. Yotam serves on the editorial boards of the Journal of the Learning Sciences and International Journal of Computer-Supported Collaborative Learning. David and Yotam talk explicitly about how much one needs to understand to be able to do QE well. They emphasize the importance of finding trustworthy colleagues with complementary skill sets.
Paper referenced: Hod, Y., Katz, S., & Eagan, B. (2020). Refining qualitative ethnographies using epistemic network analysis: a study of socioemotional learning dimensions in a humanistic knowledge building community. Computers & Education, 156, 103943.
18 Jun 2022
Week 8: Situating QE and Beyond with Ryan Baker
Dr. Ryan Baker (https://www.gse.upenn.edu/academics/faculty-directory/baker) is an Associate Professor in the Teaching, Learning, and Leadership Division at University of Pennsylvania, and studies how data can better be used to study and improve online learning. Using data from educational software, he examines how students respond to computer lessons, focusing on engagement and disengagement, and how these responses impact learning. Baker has also researched student success in MOOCs. He is working to develop the next generation of MOOCs, which will incorporate features from intelligent tutoring systems.
In this last episode, David and Ryan provide a valuable perspective on the broader learning analytics and educational data mining landscape and discuss where QE is situated in this methodological landscape.
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