Abstract
Knowledge mobilization is becoming increasingly important for research collaborations, but few methodologies support increased knowledge sharing. This study provides insights, using a reflective narrative, into a transdisciplinary knowledge-sharing investigation of the connectivity of educational research to that of other disciplines. As an exemplar for educational research, the study evaluated the use of spatial search terms from mathematics education using: 1) an initial descriptive statistical analysis combined with bi modal network analysis of highly cited articles; and, 2) a second more comprehensive unimodal analysis using bibliographic coupling networks. This iterative analytical process provided a major if surprising insight—although Education is not particularly well connected bidirectionally to many subject areas, it appears to act as a distribution centre for knowledge mobilization, providing a central hub for gathering and analysing knowledge from across disciplines in order to generate the complex system of information that underpins society.
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Notes
Because this writing is concerned with research within and communications among a number of disciplines, this article adopts the convention of capitalizing the names of those disciplines (or subject areas in Scopus) whenever there is a reference to recognized domains of inquiry. This convention is useful to distinguish between, for example, the discipline or subject area of Mathematics and the activity of learning mathematics.
All journals within the Scopus database were classified in one or more subject areas (totaling 27 at time of analysis). Neuroscience, Mathematics, and Psychology are each considered major subject areas, which may (or may not) correspond to disciplines. Mathematics Education journals are typically classified under either the subject areas of Mathematics or Social Sciences.
The internet revolution, partly through establishment of widespread individual use of hypertext and the world wide web from the mid 1990s (at least in OECD countries) sparked an increase in transdisciplinary studies globally. The year 1995 is significant as it marks the decommissioning in the USA of the National Science Foundation Network (NSFNet) and full commercialization of the Internet (Tronco 2010).
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Appendix
Appendix
Initial investigations: Delphi consensus and first network analysis
Selecting spatial search terms
The initial step in the generation of the network data was the selection of key spatial terms for use in searching for research articles with a spatial focus. In order to respond to the explosion of data from 2000 onward in the area of spatial reasoning, and to manage the size of the database, the SRSG focused on research publications since 1995 (a period approximating the time since the initial divergences and convergences of the internet revolution). An initial listing of eleven key spatial terms used across disciplines was generated based on the SRSG’s work on a spatial reasoning knowledge map (Bruce et al. 2017), the SRSG’s expertise across diverse disciplines, and web searches by SRSG members. These terms were: (a) geometry, (b) mental imagery, (c) spatial ability, (d) spatial memory, (e) spatial perception, (f) spatial reasoning, (g) spatial sense, (h) spatial skills, (i) spatial thinking, (j) spatial visualization, and (k) visual thinking.
To manage the scope of the literature review and potential network construction, the group used a modified Delphi technique to identify the top six terms in order to make the database manageable and, at the same time, to provide content validity. Delphi is an iterative and subjective approach used to synthesize differing expert opinion into a consensus (Green et al. 2007; Rowe and Wright 1999). Each member of the transdisciplinary group ranked independently what they considered to be the five most significant terms, providing an overall score for each term. The resulting six top ranked terms were as follows: spatial visualization; spatial reasoning; spatial ability; visual thinking; mental imagery; and, spatial sense. Aside from being the top six ranked terms overall, each of these six terms additionally appeared as the top six ranked terms by each group member.
Spatial terms citation searches
A search was conducted using the research database Scopus, which allowed for searches to be completed within one of the 27 subject areas. For each of the six spatial search terms, citation searches were completed by a pair of researchers using a three step “10–10–10” search process. The search process allowed for identification of the 10 most-cited or Modal Scopus Subject Areas that used this spatial term and, from this, the 10 most cited papers in each of these subject areas.
As outlined in Table 1, and diagrammatically in Fig. 5, the initial steps involved each of six researcher pairs entering a key spatial term in Scopus in alignment with the listed parameters.
The flowchart shows how each spatial search term, using the same search process, was used to find the ten most-cited or Modal Subject Areas in Scopus that used this spatial term and, from this, the most-cited paper in each of these subject areas. Using each of these most-cited papers, a list was constructed of the top ten subject areas that each of these papers was citing
Inter-rater reliability was determined from cross comparison of searches by each person in the researcher pair. Given the focus of the group on the discipline of Education, citations listed under the Scopus “Social Sciences” Subject Area were manually reviewed and those that had authors with primary alignment in the Education discipline were coded into a distinct subject area sub-category of “Social Sciences–Education”.
Using these data, and the related citation data, a spreadsheet of counts by subject area as to how they cite other subject areas was created for each of the key spatial search terms. From this data matrix, the group created a heat map of occurrences, which illustrates the concentration (darker shades meaning more activity and lighter shades indicating less activity) of the disciplines generated from the citations derived from the six spatial reasoning terms.
Small group follow-on investigations: second network analysis
Subsequent to a discussion of the limitations in the initial process, there was a realization that the following three points were significant.
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Keywords used as the basis for data collection in the initial analysis had very low frequency across all disciplines, including education, raising issues related to numbers of relevant citations.
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Based on the keywords used, the resulting citations were not necessarily relevant to spatial reasoning in the sense of Mathematics Education.
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Comparability of citations was potentially confounded by the large numbers of references in the larger disciplines, relative to Education in particular.
There was little to say that the network was specific to spatial reasoning or that we were examining educational ideas and how they are connected to other disciplines. The second process, detailed here in Table 2, was designed to overcome these limitations using a unimodal, rather than a bimodal analysis.
The second network analysis
The subsequent network analysis was based in the results of a search, again using Scopus, but using the final 32 keywords to identify refereed journal articles from 2000 to present addressing spatially relevant topics. To maintain a balance across subject areas a small working group from the SRSG identified approximately up to 2000 of the most frequently cited refereed articles in each subject area and then merged the 27 subject area citation files with the file obtained using the Mathematics Education Journal searches. The resulting dataset included approximately 38,000 unique articles uploaded using available identification of digital object identifier (doi) codes extracted from comma separated values (csv) files exported to Excel.
The unimodal analysis used bibliographic coupling analysis undertaken in VOSviewer version 1.6.6 (Van Eck and Waltman 2016), with the journal name as the unit of analysis. The minimum number of documents selected was set at 5, and the minimum number of sources was set at 0, with the subsequent illustration based on 500 sources with the greatest total link strength. On this basis, only three Mathematics Education journals were included in the final diagram (Fig. 3a, b in the actual article): ZDM Mathematics Education, total link strength of 722; Educational Studies in Mathematics, total link strength of 423; and, Mathematics Education Research Journal, total link strength of 347.
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Woolcott, G., Chamberlain, D., Hawes, Z. et al. The central position of education in knowledge mobilization: insights from network analyses of spatial reasoning research across disciplines. Scientometrics 125, 2323–2347 (2020). https://doi.org/10.1007/s11192-020-03692-2
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DOI: https://doi.org/10.1007/s11192-020-03692-2