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Quality, Rigor, and Validity in Mixed-Methods Research (Table 3)
Thu, April 13, 9:50 to 11:20am CDT (9:50 to 11:20am CDT), Chicago Marriott Downtown Magnificent Mile, Floor: 7th Floor, Grand Ballroom Salon IIISession Type: Roundtable Session
Abstract
This roundtable session explores varying perspectives on the overarching issues of quality, rigor, and validity in mixed methods research. Paper authors explore how mixed methods teams, artificial intelligence, and different forms of data collection activities impact the mixed methods process as well as doctoral students' perceptions of these key issues in mixed methods.
Sub Unit
Chair
Papers
Doctoral Students' Perceptions of Mixed-Methods Research: Value, Rigor, and Feasibility - Olivia G. Stewart, St. John's University; Kyle DeMeo Cook, Boston University
Student Predictive Analysis to Determine Program Interventions and Improve Student Performance - Nenny Aryanti Noorman, National Institute of Education - Nanyang Technological University; Sean Chen Liu, National Institute of Education - Nanyang Technological University; David Ng, Nanyang Technological University - National Institute of Education
User-Task-Tool Interactions in Second-Language Writing Assessment: A Mixed-Methods Ergonomic Analysis - Kerry J. Pusey, University of Pennsylvania; Yuko G. Butler, University of Pennsylvania
Online Response Process Procedures: Affordances and Constraints to Collect, Analyze, and Interpret Validity Information - Radhika Kapoor, Stanford University; Maria Araceli Ruiz-Primo, Stanford University; Philip Hernandez, Stanford University; Klint Kanopka, New York University