Bibliometric and Visual Insights Into Higher Education Informatization: A Systematic Review of Research Output, Collaboration, Scope, and Hot Topics

Bibliometric and Visual Insights Into Higher Education Informatization: A Systematic Review of Research Output, Collaboration, Scope, and Hot Topics

Yang An, Yushi Duan, Yuchen Zhang
DOI: 10.4018/IJICTE.340776
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Abstract

Higher education informatization (HEI) is an interdisciplinary field that examines the use and integration of information and communication technologies (ICTs) in higher education. This paper provides a bibliometric and visual analysis of the research trends, patterns, and topics in this field. Using the Web of Science database, the authors selected and analyzed 199 SCI and SSCI papers on HEI published from 2000 to 2023 by VOSviewer and CiteSpace software. The results indicate that the publication volume of HEI research has grown significantly in recent years. The author network shows the collaboration and contribution of different researchers and institutions, while the journal network reveals the multidisciplinary nature and scope of the field. The keyword network and the burst keyword analysis identify the main research themes and the emerging hot topics in HEI. The co-citation network of sources illustrates the theoretical and methodological foundations and influences of the field. The paper concludes with some implications and suggestions for future HEI research.
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Methods And Data

Research Methods

Bibliometrics is a discipline that uses quantitative methods to analyze and evaluate various aspects of scholarly literature (Ellegaard & Wallin, 2015), which originated in the late 19th century (Lawani, 1981). It mainly includes citation-based analysis and science mapping (Braam & Moed, 1991). These methods enable researchers to measure the impact of their work, compare it with others, and identify influential papers within a specific field (Li et al., 2020). When applied to the higher education informatization research, bibliometrics can provide objective, transparent, and cost-effective measurements of research impact. Moreover, it helps to visualize the evolution of the research field.

This study employs CiteSpace and VOSviewer to construct the bibliometric knowledge graph. CiteSpace is particularly good at detecting patterns and trends in literature (Chen, 2006). It offers a variety of functions to facilitate the understanding and interpretation of network patterns and historical trends. Alternatively, VOSviewer focuses on the graphical representation of bibliometric maps (Van Eck & Waltman, 2010). It is especially useful for analyzing large data sets, as it can process millions of records and offer a range of advanced features, such as a cluster detection and a visualization of temporal trends.

In conclusion, both CiteSpace and VOSviewer have unique capabilities that make them valuable tools for bibliometric research and knowledge graph construction. They enable the researchers to visualize complex bibliometric data in a meaningful and interpretable way.

Data Sources and Screening

We used the Web of Science (core collection) as our main data source, as it ensures the comprehensiveness and reliability of the data analyzed. The indices selected were SSCI and SCI-Expanded. Our search strategy incorporated the following terms:

TS=((“Higher Education” OR “College” OR “University”) AND (“Informatization” OR “Office Automation”) AND (“E-Learning” OR “Mobile Learning”) OR (“Administration” OR “Management” OR “Supervision”))

The search covered the period from January 1, 2000 to December 1, 2023, yielding a total of 2,950,001 literature records. Next, we refined our search by selecting ‘Article’ as the document type, which yielded 2,336,821 articles. Further refinement was achieved by screening the Web of Science categories and Citation Topics, leading to a selection of 2,355 articles.

However, the data obtained directly from the search formula may contain duplications or inconsistencies with the topic (Martín-Martín et al., 2018). Therefore, we performed a pre-processing step before the analysis, which involved a manual review of each article’s content (including the title and abstract) to eliminate redundant and irrelevant publications, ensuring that the selected articles were indeed related to higher education informatization research. After this rigorous screening process, we retained 199 articles for content and bibliometric mapping analysis (see Figure 1).

Figure 1.

Paper Screening and Data Cleaning Process Flowchart

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