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Measuring the processes of interdisciplinary team collaboration: Creating valid measures using a many-facet Rasch model approach
INTRODUCTION: The science of team science (SciTS) is an emerging research area that studies the processes and outcomes of team-based research. A well-established conceptual framework and appropriate methodology for examining the effectiveness of team science are critically important for promoting an...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9794954/ https://www.ncbi.nlm.nih.gov/pubmed/36590349 http://dx.doi.org/10.1017/cts.2022.472 |
Sumario: | INTRODUCTION: The science of team science (SciTS) is an emerging research area that studies the processes and outcomes of team-based research. A well-established conceptual framework and appropriate methodology for examining the effectiveness of team science are critically important for promoting and advancing collaborative and interdisciplinary research. Although many instruments have been developed and used in the SciTS field, psychometric evidence has not been routinely assessed or reported for these scales. In addition, commonly used psychometric methods were mainly limited to internal consistency and factor analysis. To fill the gaps, this study introduces a framework based on Rasch measurement theory for creating and evaluating measures for team sciences. METHODS: We illustrate the application of Rasch measurement theory through the creation of valid measures to evaluate the processes of interdisciplinary scientific teams. Data were collected from 16 interdisciplinary teams through a university-wide initiative for promoting interdisciplinary team collaboration. Psychometric evidence based on a many-facet Rasch model was obtained for assessing the quality of the measures. RESULTS: The interdisciplinary teams differed in their clarity measures. Significant differences were also found between gender groups, racial groups, and academic ranks. We reported the reliability of measures and identified items that do not fit the model and may present potential threat to validity and fairness of SciTS measures. CONCLUSION: This study shows the great potential of using Rasch measurement theory for developing and evaluating SciTS measures. Applying Rasch measurement theory produces objective measures that are comparable across individuals, interdisciplinary teams, institutions, time, and various demographic groups. |
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