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From Quantitizing to AI: Exploring Current Issues in Mixed-Methods Research Design (Table 4)
Sat, April 26, 11:40am to 1:10pm MDT (11:40am to 1:10pm MDT), The Colorado Convention Center, Floor: Ballroom Level, Four Seasons Ballroom 2-3Session Type: Roundtable Session
Abstract
As a field, mixed methods research has always been concerned with making sense of conundrums that arise wherever quantitative meets qualitative. Recently, MMR SIG has seen a simultaneous increase in proposals related to artificial intelligence (AI) and critical (Crit) research perspectives. This diverse collection of papers will prompt us to consider various ways AI can be used in mixed methods research, distinctions between quantitizing qualitative data and automated analysis, and how new Crit perspectives might help us address ethical questions inspired by concerns about who benefits from MMR infused with AI.
Sub Unit
Chair
Papers
Exploring Mixed Methods Research in Studies on ChatGPT in English Language Learning: A Systematic Review - Mazid Ul Hasan, University of Cincinnati
A Unique Mixed-Methods Design for the Analysis of Large Data Sets - Barbara Lee, Keiser University; Carol A. Isaac, Mercer University
Design, Development, and Evaluation of an AI-driven Virtual Patient System in Communication Skills Training for Healthcare Professionals: Convergent Mixed Method - Yuanyuan Gu, University of Missouri; Xinhao Xu, University of Missouri; Shangman Li, University of Missouri; Hao He, Emporia State University; Yupei Duan, University of Missouri; Jhon Bueno-Vesga, Pennsylvania State University; Sue Yun Fowler, University of Missouri; Hillary L. Claunch, University of Missouri; Jason Snyder, University of Missouri
Critical Dialectical Pluralism as a Transformative Metaparadigm for Mixed Methods Research - Anthony J. Onwuegbuzie, University of Cambridge; Sandra Schamroth Abrams, University of South Africa; Madeline L. Abrams, Green Meadow Waldorf School