How can you use mixed-methods approaches to enhance linguistic data collection?

1 What are mixed-methods approaches?

Mixed-methods approaches are research designs that integrate both qualitative and quantitative methods to answer a research question or problem. Qualitative methods are based on exploring and interpreting meanings, experiences, and perspectives of participants, while quantitative methods are based on measuring and testing variables, patterns, and relationships using numerical data. By using mixed-methods approaches, you can leverage the strengths and overcome the limitations of each method, as well as gain a deeper and richer understanding of your linguistic data.

2 Why use mixed-methods approaches for linguistic data collection?

Linguistic data collection can benefit from mixed-methods approaches for several reasons. First, you can capture the complexity and diversity of language use and behavior in different situations and groups, as well as the underlying motivations, attitudes, and beliefs of speakers. Second, you can triangulate and validate your findings by using multiple sources and types of data, such as interviews, surveys, observations, recordings, transcripts, corpora, etc. Third, you can address different aspects and levels of your research question or problem, such as description, explanation, evaluation, or intervention.

4 What are some examples of mixed-methods approaches for linguistic data collection?

Mixed-methods approaches for linguistic data collection can be used in various linguistic domains and topics. For example, a sequential explanatory approach can be employed in sociolinguistics to investigate language variation and change in a speech community. This involves collecting and analyzing quantitative data from a corpus of spoken or written language, followed by collecting and analyzing qualitative data from interviews or focus groups. In discourse analysis, a concurrent triangulation approach can be used to analyze discourse practices and strategies in a specific genre or context. This approach involves collecting and analyzing both qualitative and quantitative data from texts, recordings, or observations of discourse events, and then comparing the results to identify similarities and differences in discourse features and functions. Lastly, an embedded intervention approach can be used in pragmatics to evaluate the effectiveness of a language teaching or learning program. This requires collecting and analyzing qualitative data from pre- and post-tests, questionnaires, or feedback forms to measure the outcomes and impacts of the program, as well as embedding quantitative data from classroom interactions, assignments, or portfolios to illustrate the processes and mechanisms of the program.

5 What are some tips for using mixed-methods approaches for linguistic data collection?

When using mixed-methods approaches for linguistic data collection, it is important to plan carefully and clearly. You must be able to justify your choice of methods, explain your rationale and logic, and describe your procedures and steps in detail. Additionally, you should select and apply appropriate and reliable tools and techniques for data collection and analysis that suit your methods, data, and research objectives. Lastly, you should communicate your mixed-methods approach effectively and transparently, reporting accurately and comprehensively while highlighting your findings and implications in a coherent and convincing way.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?