Creating Transparency in Team Based Qualitative Analysis

Format Type

Plenary

Format Type

Workshop

Start Date

14-1-2021 3:50 PM

End Date

14-1-2021 4:40 PM

Abstract

Qualitative data adds depth and perspective to research questions and provides a richness that cannot be obtained solely from quantitative data. In large-scale qualitative research projects, having multiple analysts is a necessity, but ensuring transparency, uniformity, and dependability in multi-person analysis can prove challenging—particularly when team members have different disciplinary backgrounds. This workshop will discuss how the Teacher Quality Partnerships (TQP) project approached hundreds of hours of interview data using James Spradley’s Developmental Research Sequence (DRS). TQP is a partnership between the University of Central Florida (UCF) and Orange County Public Schools (OCPS) designed to recruit, prepare, and sustain highly effective teachers with specific foci in mathematics to support students with diverse learning needs. Qualitative data from the Teacher Quality Partnerships (TQP) will be used for demonstration purposes. The workshop will begin with a broader discussion of the strengths and potential pitfalls to avoid in team-based qualitative research and then move into the mechanics of applying the DRS Method. Participants will together practice skills demonstrated during the workshop and will learn strategies to capitalize on the strengths of an interdisciplinary qualitative research team. They will also learn techniques to help ensure transparency and reliability in their own future research.

Learning Objectives:

  1. Participants will increase their understanding of Spradley’s DRS Method.

  2. Participants will understand how to ensure transparency in their work.

  3. Interdisciplinary research teams will gain an understanding of how to increase the reliability of their results.

  4. Participants will have the opportunity to practice data analysis using the DRS Method.


Keywords

Qualitative research, interdisciplinary research teams, transparency and reliability, James Spradley’s Developmental Research Sequence (DRS)

This document is currently not available here.

Share

COinS
 
Jan 14th, 3:50 PM Jan 14th, 4:40 PM

Creating Transparency in Team Based Qualitative Analysis

Qualitative data adds depth and perspective to research questions and provides a richness that cannot be obtained solely from quantitative data. In large-scale qualitative research projects, having multiple analysts is a necessity, but ensuring transparency, uniformity, and dependability in multi-person analysis can prove challenging—particularly when team members have different disciplinary backgrounds. This workshop will discuss how the Teacher Quality Partnerships (TQP) project approached hundreds of hours of interview data using James Spradley’s Developmental Research Sequence (DRS). TQP is a partnership between the University of Central Florida (UCF) and Orange County Public Schools (OCPS) designed to recruit, prepare, and sustain highly effective teachers with specific foci in mathematics to support students with diverse learning needs. Qualitative data from the Teacher Quality Partnerships (TQP) will be used for demonstration purposes. The workshop will begin with a broader discussion of the strengths and potential pitfalls to avoid in team-based qualitative research and then move into the mechanics of applying the DRS Method. Participants will together practice skills demonstrated during the workshop and will learn strategies to capitalize on the strengths of an interdisciplinary qualitative research team. They will also learn techniques to help ensure transparency and reliability in their own future research.

Learning Objectives:

  1. Participants will increase their understanding of Spradley’s DRS Method.

  2. Participants will understand how to ensure transparency in their work.

  3. Interdisciplinary research teams will gain an understanding of how to increase the reliability of their results.

  4. Participants will have the opportunity to practice data analysis using the DRS Method.