[Rasch] A Scientometric Review of Rasch Measurement
trevor.bond at jcu.edu.au
Fri Oct 25 11:08:31 AEDT 2019
Dear Rasch colleagues
Aryadoust Vahid, Tan Hannah Ann Hui, & Ng Li Ying have published an article that should be of interest to many of our RM colleagues:
A Scientometric Review of Rasch Measurement: The Rise and Progress of a Specialty
ABSTRACT=A recent review of the literature concluded that Rasch measurement is an influential approach in psychometric modeling. Despite the major contributions of Rasch measurement to the growth of scientific research across various fields, there is currently no research on the trends and evolution of Rasch measurement research. The present study used co-citation techniques and a multiple perspectives approach to investigate 5,365 publications on Rasch measurement between 01 January 1972 and 03 May 2019 and their 108,339 unique references downloaded from the Web of Science (WoS). Several methods of network development involving visualization and text-mining were used to analyze these data: author co-citation analysis (ACA), document co-citation analysis (DCA), journal author co-citation analysis (JCA), and keyword analysis. In addition, to investigate the inter-domain trends that link the Rasch measurement specialty to other specialties, we used a dual-map overlay to investigate specialty-to-specialty connections. Influential authors, publications, journals, and keywords were identified. Multiple research frontiers or sub-specialties were detected and the major ones were reviewed, including “visual function questionnaires”, “non-parametric item response theory”, “valid measures (validity)”, “latent class models”, and “many-facet Rasch model”. One of the outstanding patterns identified was the dominance and impact of publications written for general groups of practitioners and researchers. In personal communications, the authors of these publications stressed their mission as being “teachers” who aim to promote Rasch measurement as a conceptual model with real-world applications. Based on these findings, we propose that sociocultural and ethnographic factors have a huge capacity to influence fields of science and should be considered in future investigations of psychometrics and measurement. As the first scientometric review of the Rasch measurement specialty, this study will be of interest to researchers, graduate students, and professors seeking to identify research trends, topics, major publications, and influential scholars.
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