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This interactive, full-day workshop gathers researchers from diverse fields to explore the use of large language models (LLMs) for qualitative data analysis. Participants will dive into cutting-edge research, discussing methodologies and tools that enhance automated qualitative analysis across educational and research contexts. We aim to facilitate collaboration, build shared resources, and collectively address the challenges posed by LLMs in education, such as data privacy and ethical concerns.
The workshop includes presentations, hands-on activities, and discussions about the role of AI in qualitative research. Attendees will gain insights into current applications, best practices, and the potential future of LLM-driven qualitative analysis. A key output will be a plan for conducting a systematic review of LLM applications for qualitative data analysis, fostering community engagement and resource development.
Call for Workshop Proposals
We invite researchers, practitioners, and scholars to submit a 500-800 word abstract detailing their work. Submissions should focus on the use of large language models (LLMs) or AI for qualitative analysis in educational or related contexts. Please include an overview of the research context, methodology, tools used, and any key findings or challenges. We encourage innovative, interdisciplinary approaches and welcome both completed and in-progress research. All abstracts will undergo a blind peer-review process by our program committee. Selected authors will be invited to present their work during the workshop.
Submissions should be emailed to ryanbaker.handin2@gmail.com no later than December 4, 2024 AOE (anywhere on Earth). Please note that all submissions will be single-blinded
Possible themes include:
Applications of Large Language Models (LLMs) in Qualitative Data Analysis
Comparing Traditional NLP Methods and LLMs for Qualitative Coding
Cross-Language Qualitative Analysis Using AI Tools
Ethical Considerations in AI-Driven Qualitative Research
Innovative Uses of AI for Thematic Coding and Codebook Development
Ensuring Validity and Reliability in AI-Assisted Qualitative Research
Interdisciplinary Approaches to AI-Driven Qualitative Research
Scaling Qualitative Analysis with AI in Large-Scale Education Datasets
Human-AI Collaboration in Qualitative Research
Emerging Tools and Technologies for AI-Assisted Qualitative Research
If selected, accepted abstracts will be presented during the workshop in the form of short talks, followed by discussions and breakout sessions. Presentations will be approximately 15 minutes in length, allowing presenters to share their research context, methodologies, and findings related to the use of LLMs in qualitative data analysis. Presenters are encouraged to discuss both the theoretical and practical implications of their work, including any challenges faced in applying AI techniques to qualitative research.
Accepted abstracts will NOT be included in the workshop proceedings. Workshop materials, including presentation slides and recordings, will also be accessible online via this workshop site and published through CEUR-WS, ensuring broad dissemination of the work presented. Authors may also have the opportunity to collaborate on a collective review or position paper following the workshop, focusing on the state of the field and future directions for LLMs in qualitative research.
Important dates:
December 4, 2024, 11:59pm AOE: Deadline for submission of papers to individual workshops that issue calls
Dec 20, 2024: Notification of acceptance for papers submitted to individual workshops
March 4, 2025 (9am-5pm) : In-person workshop
Workshop Organizers
Amanda Barany
University of Pennsylvania (amanda.barany@gmail.com)
Ryan S. Baker
University of Pennsylvania (ryanshaunbaker@gmail.com)
Andrew Katz
Virginia Tech Engineering Education (akatz4@vt.edu)
Jionghao Lin
Carnegie Mellon University & Monash University (jionghal@andrew.cmu.edu)
Program Committee:
Anthony Botelho, The University of Florida College of Education
Ashish Gurung, Carnegie Mellon University
Yoon Jeon (YJ) Kim, University of Wisconsin-Madison
Ayaz Karimov, University of Jyväskylä
Yi-Chieh (EJ) Lee, National University of Singapore
Ha Nguyen, University of North Carolina at Chapel Hill
Jeanne McClure, North Carolina State University
Jaclyn Ocumpaugh, University of Pennsylvania
Luc Paquette, University of Illinois
Saríah Lopez-Fierro, Utah State University
Workshop Registration
Registration information will be shared soon. All LAK25 participants are welcome to register for the workshop, regardless of whether they submit or present an abstract. Please email the workshop organizers with any questions!
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