On the Problems of Honorary Work in German Sports Clubs–A Qualitative-Dominated Crossover Mixed Methods Study

2020 ◽  
Vol 12 (3) ◽  
pp. 335-353
Author(s):  
Stefan König ◽  
Steffen Greve
Keyword(s):  
Mixed Methods ◽  
Social Life ◽  
Mixed Methods Research ◽  
Multiple Correspondence Analysis ◽  
Numerical Data ◽  
Mixed Methods Study ◽  
Data Conversion ◽  
Multidimensional Data ◽  
Data Set ◽  
Sports Clubs

In crossover mixed analyses, one form of data is analyzed applying techniques that usually are associated with the alternative paradigm in order to yield a higher level of data integration. This basic principle is implemented in equal-status studies and in quantitative- as well as in qualitative-dominated approaches. Focusing on the latter, data conversion has been a vital issue of mixed methods research for many years, likely because it entails quantitizing narrative data to provide a basis for descriptive and inferential statistical analyses. Referring hereon, this article presents a qualitative-dominated crossover mixed methods study dealing with the problem of honorary work in German sports clubs, an issue that has been intensively discussed in sports and in other areas of society due to some alarming developments in social life. In this process, the issue of honorary work is utilized as an example of demonstrating a methodology. The design presented in this article involved use of a crossover analysis that converts narrative data into numerical data and involves analysis of the new data set using multiple correspondence analysis (MCA) with the aim of discovering patterns among the multidimensional data. In turn, these patterns are interpreted against the background of the first qualitative strand to enhance our understanding. Thus, this study is to be referred to as qualitative-dominated because the sets of qualitative analyses are more comprehensive and important and the researchers have taken a stance that is constructivist, while concurrently believing that quantitative data adds value to this approach.

Students’ General Knowledge of the Learning Process: A Mixed Methods Study Illustrating Integrated Data Collection and Data Consolidation

2016 ◽  
Vol 12 (2) ◽  
pp. 182-203 ◽  
Author(s):  
Joke H. van Velzen
Keyword(s):  
Mixed Methods ◽  
Data Collection ◽  
Learning Process ◽  
Mixed Methods Research ◽  
Mixed Methods Study ◽  
Data Sets ◽  
General Knowledge ◽  
Data Set ◽  
Data Consolidation ◽  
New Research

There were two purposes for this mixed methods study: to investigate (a) the realistic meaning of awareness and understanding as the underlying constructs of general knowledge of the learning process and (b) a procedure for data consolidation. The participants were 11th-grade high school and first-year university students. Integrated data collection and data transformation provided for positive but small correlations between awareness and understanding. A comparison of the created combined and integrated new data sets showed that the integrated data set provided for an expected statistically significant outcome, which was in line with the participants’ developmental difference. This study can contribute to the mixed methods research because it proposes a procedure for data consolidation and a new research design.

scholarly journals Quantitizing and qualitizing (im-)possibilities in mixed methods research

2018 ◽  
Vol 11 (2) ◽  
pp. 205979911878902 ◽  
Author(s):  
Jean Providence Nzabonimpa
Keyword(s):  
Mixed Methods ◽  
Quantitative Data ◽  
Mixed Methods Research ◽  
Empirical Studies ◽  
Methodological Issue ◽  
Numerical Data ◽  
Data Conversion ◽  
New Paradigm ◽  
Two Phase ◽  
Mixed Analysis

Mixed methods research has gained momentum over the past decade, but critics rightly charge that the integration of qualitative and quantitative data remains an unresolved methodological issue. While each of the dualistic and canonized methodological paradigms has its own way of handling analysis, researchers in mixed methods as a new paradigm have invested considerable efforts in more complex mixed analysis. They use the quantitizing of qualitative data and qualitizing of quantitative data as the strategies to effect data integration in mixed methods research. While attempts have been made to achieve quantitizing and qualitizing of data, few empirical studies have been conducted in a two-phase convergent parallel mixed methods design to investigate such data conversion approaches, especially dichotomization, within a single inquiry. To contribute to this ongoing methodological quest, this article explores the possibilities and impossibilities offered by either strategy to convert narratives into numerical data and numerical data into narratives.

Construct the Logic Model and Research Design (Step 3)

2019 ◽  
pp. 81-88
Author(s):  
Edmund M. Ricci ◽  
Ernesto A. Pretto ◽  
Knut Ole Sundnes
Keyword(s):  
Mixed Methods ◽  
Research Design ◽  
Mixed Method ◽  
Disaster Response ◽  
Mixed Methods Research ◽  
Research Question ◽  
Logic Model ◽  
Data Set ◽  
Evaluation Team ◽  
Mixed Method Design

A ‘mixed-methods’ research design, based upon the categories contained in a disaster response logic model, is suggested as the best approach to capture the complexities of the medical and public health disaster response experience. A mixed-methods design allows the evaluation team to collect and combine data from direct observation, medical records, interviews with victims, health professionals, family and friends of victims, public safety officials, other government and non-governmental officials and from public documents. Validation in a mixed-method design is based upon the concept of triangulation. The term triangulation is used in behavioral research to describe the process of obtaining data from three or more different sources and then comparing the findings to assess consistency across sources. In this design, both qualitative and quantitative data are collected and then merged during the analysis phase. Each data set is used to validate and enhance the other in order to improve the validity of the conclusions reached and the recommendations that follow. However, not all data need be combined. The mixed-method design allows for the analysis of certain types of data separately and then applied to the appropriate research question because there may be no appropriate comparative data.

scholarly journals The Titanic Game: Introducing Game Heuristics to Mixed Methods Theorizing and Data Analysis

2019 ◽  
Vol 14 (4) ◽  
pp. 522-544
Author(s):  
Jörg Stolz ◽  
Anaïd Lindemann
Keyword(s):  
Mixed Methods ◽  
Data Analysis ◽  
Mixed Methods Research ◽  
Quantitative Model ◽  
Game Studies ◽  
Data Set ◽  
Social Games ◽  
Mixed Methods Approach ◽  
Survival Probabilities ◽  
Set Up

Despite tremendous interest in social games and game studies, the potential of game heuristics for the field of mixed methods remains unknown. This article introduces game heuristics to mixed methods research, showing how it was used in a specific study on the survival probabilities on the Titanic. Specifically, we describe how game heuristics was used to create the explanandum, code and interpret the qualitative material, and set up and interpret the quantitative model. Furthermore, we show and explicate how game heuristics was used to construct seven types of meta-inferences. The Titanic data set is especially interesting, since it is routinely used for statistical mono-method teaching; however, it can be shown that a mixed methods approach leads to a better explanation.

A Systematic Methodological Review of Hierarchical Linear Modeling in Mixed Methods Research

2020 ◽  
pp. 155868982093788
Author(s):  
Kirstie L. Bash ◽  
Michelle C. Howell Smith ◽  
Pam S. Trantham
Keyword(s):  
Mixed Methods ◽  
Hierarchical Linear Modeling ◽  
Mixed Methods Research ◽  
Quantitative Methods ◽  
Linear Models ◽  
Mixed Methods Study ◽  
Linear Modeling ◽  
Methodological Review ◽  
Design Choice

The use of advanced quantitative methods within mixed methods research has been investigated in a limited capacity. In particular, hierarchical linear models are a popular approach to account for multilevel data, such as students within schools, but its use and value as the quantitative strand in a mixed methods study remains unknown. This article examines the role of hierarchical linear modeling in mixed methods research with emphasis on design choice, priority, and rationales. The results from this systematic methodological review suggest that hierarchical linear modeling does not overshadow the contributions of the qualitative strand. Our study contributes to the field of mixed methods research by offering recommendations for the use of hierarchical linear modeling as the quantitative strand in mixed methods studies.

A Mixed Methods Study of K–12 Influences on College Participation for Students With Disabilities

2020 ◽  
Vol 43 (2) ◽  
pp. 101-114
Author(s):  
Elisabeth L. Kutscher ◽  
Elizabeth D. Tuckwiller
Keyword(s):  
Mixed Methods ◽  
Students With Disabilities ◽  
Postsecondary Education ◽  
Mixed Methods Research ◽  
Multiple Correspondence Analysis ◽  
College Participation ◽  
Quantitative Results ◽  
Education Participation ◽  
Transformative Mixed Methods ◽  
K 12

This study investigated K–12 experiences individuals with disabilities perceived as influencing their transition to and participation in postsecondary education. Using a convergent transformative mixed methods research design, the study integrated findings from interviews and surveys ( n = 13) using multiple correspondence analysis. Qualitative analyses yielded eight K–12 facilitators of postsecondary education participation. Quantitative results showed participants reported access to at least one previously identified high school predictor, high levels of self-determination, and neutral identification with a disability community. Finally, integrated findings revealed that endorsement of facilitators was associated with experiencing a challenging transition to postsecondary education. Research and practice implications are discussed.

scholarly journals Quality Reporting of Mixed Methods Research in Tourism-Related Studies

2021 ◽  
Vol 10 (10(6)) ◽  
pp. 1794-1810
Author(s):  
CH Van Heerden
Keyword(s):  
Mixed Methods ◽  
Mixed Methods Research ◽  
Reporting Quality ◽  
International Standards ◽  
Future Research ◽  
Quality Of Reporting ◽  
Data Set ◽  
Postgraduate Students ◽  
Quality Reporting

The aim of this study is to gain scientific insight into internationally-accepted criteria for quality reporting of mixed methods research (MMR). Articles published post-2012 in a particular journal, which referred to “mixed methods” and “tourism”, and reported that qualitative and quantitative data were collected, were drawn from Google Scholar and Scopus. The reporting quality of these studies was analysed according to the GRAMMS framework (Good Reporting of a Mixed Methods Study). Most of the articles in the data set did not report on all the elements embedded in GRAMMS. It must not be seen as a reflection of the quality of the MMR design itself, nor is the study flawed. It indicates gaps in the reporting of important MMR elements that could be addressed in future research. Exemplars were identified that could serve as case studies for researchers in terms of the quality of reporting on MMR. Editorial boards should adopt guidelines on how MMR could be presented in articles submitted to their journals. These guidelines could assist authors in preparing their articles to conform to international standards on the reporting of MMR studies. Peer reviewers should use the guidelines to judge the quality of reporting on MMR methodology in articles under review. This study could also serve as a future reference for researchers, postgraduate students and supervisors who aim to incorporate MMR in their research.

Do Sociology Courses Make More Empathetic Students? A Mixed-Methods Study of Empathy Change in Undergraduates

2019 ◽  
Vol 47 (4) ◽  
pp. 284-302 ◽  
Author(s):  
Ashley Rockwell ◽  
Chris M. Vidmar ◽  
Penny Harvey ◽  
Leanna Greenwood
Keyword(s):  
Mixed Methods ◽  
Research Design ◽  
Undergraduate Students ◽  
Mixed Methods Research ◽  
Mixed Methods Study ◽  
Student Surveys ◽  
Introductory Sociology ◽  
Empathy Development

Assessing course goals is often challenging; assessing an abstract goal, like empathy, can be especially so. For many instructors, empathy is central to sociological thinking. As such, fostering empathy in students is a common course goal. In this article, we report the initial findings of a semester-long assessment of empathy change in undergraduate students ( N = 619). We employ a mixed-methods research design that utilizes qualitative instructor data to determine independent instructor-level variables and student surveys to measure student empathy change. We compare empathy change between students enrolled in introductory sociology classes to students not enrolled in sociology classes and test which student and instructor variables predict empathy change. We find that students taking sociology classes have positive empathy change compared to those who do not. We interpret these findings as evidence that study of sociology promotes empathy development and discuss implications for the classroom and further research.

Using Mixed Methods Research to Better Understand Pediatric Feeding Disorder

2020 ◽  
Vol 5 (6) ◽  
pp. 1623-1630
Author(s):  
Kelsey L. Thompson ◽  
Wanqing Zhang
Keyword(s):  
Mixed Methods ◽  
Mixed Methods Research ◽  
Research Question ◽  
Interdisciplinary Teams ◽  
Mixed Methods Study ◽  
Feeding Disorder ◽  
Qualitative And Quantitative ◽  
Heterogenous Population ◽  
Pediatric Feeding ◽  
Study Designs

Purpose Mixed methods research is a relatively new, but growing, research methodology with particular relevance to speech-language pathologists because of its utility in translating research into practice. Mixed methods research involves collection of both qualitative and quantitative data, which is integrated to gain a deeper understanding of a research question, particular population or intervention, or to develop a tool. In particular, pediatric feeding disorder (PFD) research stands to benefit from this methodology to comprehensively and holistically report on this population. Conclusions This article focuses on introducing researchers new to mixed methods, as well as clinicians, to the four basic mixed methods study designs and considerations. To establish a foundational understanding, examples of published work specific to PFD are incorporated and a framework for understanding mixed method study design is proposed. Then, the four designs are examined from the lens of critical appraisal, so that clinicians and researchers are well prepared to critically evaluate mixed methods studies. Finally, applications of mixed methods to PFD are explored, with a commentary on how published examples could be extended using mixed methods designs. This article provides researchers and clinicians with a basic understanding of mixed methods as well as a clear avenue for its application to PFD. Mixed methods has the potential to advance our understanding of the heterogenous population PFD impacts, improve our use of interdisciplinary teams, examine holistic interventions, and develop tools for clinical and research use.

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