Transforming Researchers Through Trans-Methodological Instruction

Location

DeSantis Room 1052

Format Type

Plenary

Format Type

Paper

Start Date

16-1-2020 10:15 AM

End Date

16-1-2020 10:35 AM

Abstract

Many qualitative researchers have shared or presented strategies for re-educating individuals who were primarily trained in quantitative or statistical research methods. The goals of these strategies include providing quantitative scholars with instruction in qualitative design and analysis, and increasing their appreciation of the value of qualitative inquiry to address complex issues in social research. Strategies to improve qualitative researchers' appreciation and thoughtful use of quantitative methods are useful for their potential to address similar goals. Overall benefits of cross or trans-methodological researcher training include increases in researchers' methodological fluency, improvements in shared understanding, and enhancements in researchers' abilities to collaborate effectively. Challenges include lack of researcher comfort with or confidence in working with alternative methodologies.

The effectiveness of trans-methodological research instruction might be enhanced by use of familiar concepts. To this end, the purpose of this paper presentation is to demonstrate a comparison among three processes from statistical modeling: 1) Use of model fit indices to assess multi-variable regression models; 2) Use of latent variables in the measurement modeling phase of structural equation modeling; 3) Applications of axes rotations in factor analysis, with select methods associated with qualitative inquiry, including: A) Thematic analysis; B) Grounded theory; C) Reflexive and deconstructive approaches to data analysis, to illustrate aspects of conceptual similarity. The content of this presentation is intended to be informative while the process is intended to potentially serve as a model for delivering instruction on other topics in trans-methodology training. Please note: no prior statistical knowledge among attendees is presumed.

Keywords

research instruction, qualitative, quantitative, trans-methodology

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Jan 16th, 10:15 AM Jan 16th, 10:35 AM

Transforming Researchers Through Trans-Methodological Instruction

DeSantis Room 1052

Many qualitative researchers have shared or presented strategies for re-educating individuals who were primarily trained in quantitative or statistical research methods. The goals of these strategies include providing quantitative scholars with instruction in qualitative design and analysis, and increasing their appreciation of the value of qualitative inquiry to address complex issues in social research. Strategies to improve qualitative researchers' appreciation and thoughtful use of quantitative methods are useful for their potential to address similar goals. Overall benefits of cross or trans-methodological researcher training include increases in researchers' methodological fluency, improvements in shared understanding, and enhancements in researchers' abilities to collaborate effectively. Challenges include lack of researcher comfort with or confidence in working with alternative methodologies.

The effectiveness of trans-methodological research instruction might be enhanced by use of familiar concepts. To this end, the purpose of this paper presentation is to demonstrate a comparison among three processes from statistical modeling: 1) Use of model fit indices to assess multi-variable regression models; 2) Use of latent variables in the measurement modeling phase of structural equation modeling; 3) Applications of axes rotations in factor analysis, with select methods associated with qualitative inquiry, including: A) Thematic analysis; B) Grounded theory; C) Reflexive and deconstructive approaches to data analysis, to illustrate aspects of conceptual similarity. The content of this presentation is intended to be informative while the process is intended to potentially serve as a model for delivering instruction on other topics in trans-methodology training. Please note: no prior statistical knowledge among attendees is presumed.