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Challenges in Doing Mixed-Methods Grounded Theory Research

Snurb — Thursday 28 November 2024 15:14
ACSPRI 2024 |

The second speaker in this ACSPRI 2024 conference session is Qian Eileen Yang, whose research used grounded theory. Grounded theory has evolved from its traditional models through an evolved version towards constructivist grounded theory as developed by Charmaz; while original formulations built only on the data gathered for the study, the latter puts the literature review first in order to enable the scoping of the research work against existing knowledge.

Grounded theory is an inductive approach that builds theory from the research, without preconceived hypotheses or theories; it is said to be suitable for both qualitative and quantitative, and indeed for mixed-methods, research. Eileen’s work explored international postgraduate coursework students’ navigation of academic writing expectations at Australian universities, and used quantitative approaches to reach a larger sample of the target population while gaining further, deeper insights into participants’ experiences and views from qualitative data.

Key challenges here include defining the typology of such mixed-methods research – how quantitative or qualitative is it going to be, and what components should dominate? Second, what instruments are to be used, how can they be tested, and how do they evolve through an iterative design, piloting, and application process? Third, theoretical sampling requires a selection of participants, cases, or contexts in order to develop a rich range of theoretical concepts (and must balance the project’s ambition with considerations about its practicality).

A fourth challenge is data collection and analysis. This is concurrent, iterative, and comparative: qualitative and quantitative data are collected in parallel, and cross-influence each other. Fifth, integrating the various findings from these different components is nontrivial, given these complexities. Sixth, the theory construction that should take place at the end may be seen as too ambitious, especially in smaller-scale studies; it must therefore be phrased and contextualised carefully in order not to overclaim the general applicability of such work.

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