• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar

information for practice

news, new scholarship & more from around the world


advanced search
  • gary.holden@nyu.edu
  • @ Info4Practice
  • Archive
  • About
  • Help
  • Browse Key Journals
  • RSS Feeds

Integrated Data Collection in Q Methodology: Using ChatGPT From Concourse to Q-sample to Q-sort

Journal of Mixed Methods Research, Ahead of Print.
Data collection in mixed methods research (MMR) can present challenges. To demonstrate the inherently mixed data collection within Q methodology (Q-technique), we start by generating a concourse of subjective statements with ChatGPT. A structured Q-sample is selected from the concourse using Fisher’s Design of Experiments which came from agricultural research and involves small sample theory and variance design. The process of the Q-sort involves each participant placing the Q-sample’s numbered subjective items into a continuum (grid) of Most Like to Most Unlike their view on the topic. Thus, the participants transform the subjective statements into a qualitative–quantitative hybrid representation of their inner subjectivity. The contribution to MMR is continuing the dialogue for integrated data collection via a specific example.

Read the full article ›

Posted in: Journal Article Abstracts on 08/05/2024 | Link to this post on IFP |
Share

Primary Sidebar

Categories

Category RSS Feeds

  • Calls & Consultations
  • Clinical Trials
  • Funding
  • Grey Literature
  • Guidelines Plus
  • History
  • Infographics
  • Journal Article Abstracts
  • Meta-analyses - Systematic Reviews
  • Monographs & Edited Collections
  • News
  • Open Access Journal Articles
  • Podcasts
  • Video

© 1993-2025 Dr. Gary Holden. All rights reserved.

gary.holden@nyu.edu
@Info4Practice