Ongoing processes of globalization within education have significantly shaped the goals of schooling, leading to what some scholars have termed the global turn in education (Mannion, Biesta, Priestley, & Ross, 2011). The global turn can be seen in curricular contents, policy, and within classrooms around the world (Van der Wende, 2007); whereas education once aimed to position students to take up higher education and future employment in the local sphere and construct a  unified national identity, attempts are now being made to introduce cosmopolitan and global ideas, particularly in Europe (Bromley, 2009). Schooling now, more than ever, seeks to prepare students to take part in the ‘global competition’ for future education and employment destinations, participate in ‘global problem solving,’ and, broadly, be better equipped to face the challenges that globally connected contemporary societies must engage with (Dill, 2013; Goren & Yemini, 2016; 2017a;b; 2018; Reilly & Niens, 2014; Vidovich, 2004).

Both practitioners and the research literature refer to the multi-faceted manifestations of the global turn within schools as promoting ‘global citizenship education’ (GCE), teaching ‘21^st-century skills,’ developing ‘intercultural competencies,’ and offering a ‘cosmopolitan education.’ These terms are all used synonymously in many cases (Caruana, 2014; Kerkhoff, 2017; Yemini, Tibbitts, & Goren, 2019); policy-makers and scholars take into account different contextual factors when choosing which to employ, but rarely present or justify how this decision is made. Thus, the meanings associated with each term within the context being studied are often unclear and why a particular term has been chosen over another not articulated.

In this project, we use an innovative, inter-disciplinary methodology integrating the use of Big Data, artificial intelligence (AI) in the form of natural language processing (NLP), and network analysis and visualization, alongside qualitative data analysis, to examine the similarities and differences in the academic scholarship surrounding four of the key concepts that are central to the discourse surrounding the global turn in education (Sellar, & Lingard, 2013) and educational governance (Mannion, Biesta, Priestley, & Ross, 2011): 21^st century skills, GCE, education for intercultural competence, and cosmopolitan education. This pioneering approach enables us to create the first comprehensive network of the large, sometimes disparate body of literature in this field. This approach therefore enables us to identify the central foci of research within each concept and to critically demonstrate their inter-relationships. First, we identified terms that are central to the academic discourses surrounding each of the four concepts for which data were collected, as well as the relationship between the concepts themselves. Through this process we were able to identify some unique trends within, and characteristics of, the literature surrounding each of the concepts, as well as capture the overarching themes that are present in each of the networks, thus providing a comprehensive, broad, large-scale view of the current landscape of research related to the global turn in education. We show, using four key concepts, how the methodology presented here can be useful to scholars embarking on research in complex fields, and in identifying core terms, caveats, and  strands of research in large bodies of literature.

Our method (developed by Blumenfeld-Lieberthal et al., 2017) is based on several stages; namely, data collection, NLP analysis, network creation, network visualization, and supplementary qualitative analysis (See figure 1 for overview). First, we used one of the three largest databases for peer-reviewed education research, the Education Resources Information Center (ERIC), to screen academic peer-reviewed papers published in the last five years, concentrating on each of the four terms included in our analysis: GCE (N=226), 21st century skills (N=168), intercultural competencies (N=191), and cosmopolitan education (N=159). The data-collection process followed Fink’s (2010) guidelines for systematic reviews, which emphasize rigor and reproducibility. Once we had assembled the database of all searchable articles, we followed the methodology developed by Blumenfeld-Lieberthal and colleagues (2017) to continue the analysis. First, we used the Open Calais software developed by Thomson Reuters, which utilizes machine learning and NLP-driven algorithms to derive topics (‘social tags’) from each of the individual articles in the cohort . Finally, we used the network visualization and exploration software Gephi to perform our analysis and visualize its results. To detect better-connected nodes that form communities within our networks (and depict topics that are more closely related to one another within the entire examined corpus), we used the Gephi embedded algorithm based on the Louvain Method (Blondel, Guillaume, Lambiotte, & Lefebvre, 2008) for community detection. The creation of a cluster or ‘community’ (as they are called throughout this review) indicates that the nodes assigned the same color in the visualization are linked to enough unique nodes to constitute a separate strand of literature. The size of each individual node in the visualization is a function of the number of links the term has and the number of times it appears in the dataset (when counted once per article). Thus, larger nodes indicate topics that appear in multiple articles. Due to the descriptive nature of the network analysis and visualizations, we supplemented the analysis using a deductive qualitative approach (Morse & Niehaus, 2009). We used qualitative analysis to provide examples for each of the communities in the networks and to highlight the unique manifestations of the themes we found across all of the networks.

In showing the individual composition of each network, our review reveals some aspects that are unique to the literature surrounding each of the concepts we chose, such as the extent to which they are shaped by supranational organizations. The abundance of mentions of terms related to the OECD, PISA, testing, and assessment in the 21st century skills network, for example, provides evidence for the successful dissemination of the OECD’s educational goals through academic literature. The variety of terms in the GCE network that are associated with UNESCO and its various development goals, as well as the grouping of these terms in the same community as environmental education (a supposedly neutral field of knowledge), similarly points to a successful process of dissemination. Thus, this review calls attention to the political, economic, and supra-national bodies that can influence the language chosen and thus the concepts employed in nationally based policy, practice, and research. The newly introduced measurement of global competencies in the Program for International Student Assessment (PISA), alongside the simultaneous inclusion of GCE in UNESCO’s Sustainable Development Goals (SDGs), means that ensuring we have a coherent evidence base, which understands how these terms are differentially engaged with, but linked is ever more critical. Through this review, we hope to consolidate much of the scholarship related to the skills and dispositions associated with education’s global turn, by providing a blueprint for scholars embarking on related research, enabling them to reflect on the concepts and specific stands of literature to which their work relates and providing a clear account of the unique features and characteristics of each body of literature. More broadly, we aim to engage researchers from other disciplines with this novel methodology, shedding light on a new way to include big data, NLP and artificial intelligence in any field.

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