A Scientometric Study of Digital Literacy, ICT Literacy, Information Literacy, and Media Literacy

The data for this study was downloaded from the WoS. The articles were retrieved by using the Boolean search method with the four keywords with “OR” between them: “digital literacy,” “ICT literacy,” “information literacy,” “media literacy.” These keywords were selected based on previous studies (Ahn, 2017; Koltay, 2011). More specifically, “digital literacy,” “information literacy,” and “media literacy” were selected since they were prevalently used keywords, according to Koltay (2011). “ICT literacy” was additionally included as it was adopted in the Korean national guideline (Ahn, 2017). Other related keywords (e.g. e-literacy and computer literacy) may be counted; however, we only focus on the four selected keywords in the present study since they are prevailing concepts. The publication period of the downloaded articles ranged from the year 2000 to the date the data was downloaded, November 13^th, 2018. A total of 3,424 articles were retrieved. Of them, journal articles in education-related sections (education educational research, education scientific discipline, psychology educational, and education special) were chosen for the analysis in this research. After the selection process, the final dataset had 728 journal articles with a total of 22,570 references.

Scientometrics is a scientific method to quantitatively measure research influence (Garfield, 2006). The present study retrieved journal articles and investigated the articles as well as the publications cited in them in terms of keyword, co-authorship, and cluster.

Three different types of keywords (author keywords, topic keywords, and co-occurring keywords) were examined. First, author keywords were determined by the authors of the articles. Second, topic keywords were suggested by the WoS to illustrate the research topics of the articles reviewed. That is, while author keywords are the terms that the authors of the articles indicate commonly below the abstracts of the articles, topic keywords are the terms that the WoS determines by using an algorithm to explore the reference and bibliographic information (Clarivate, 2020). We included both author and topic keywords in our data analysis due to the different coverage of each. Third, keywords that co-occur in the same articles were analyzed to discover research themes and clusters.

VOSviewer version 1.6.9 (CWTS Leiden, 2018) was used to analyze the co-occurring keywords through natural language processing algorithms. For the cluster analysis of the co-occurring keywords, the unified approach of mapping and clustering methods was adopted to categorize the clusters based on similar content and topics and illustrate the weighted cluster network according to the strength of the association between the keywords (Waltman, van Eck, & Noyons, 2010). The keywords that have links with other keywords (co-occurrence) and the clusters of those keywords will be underlined in this paper by the strength of linkage, which shows the frequency of the co-occurrences. Also, a list of the individual keywords that have the most links with other keywords will be presented (van Eck & Waltman, 2014).

VOSviewer version 1.6.9 (CWTS Leiden, 2018) was also utilized to figure out the co-authors and their clusters based on the information about author name, organization, and country/region (van Eck & Waltman, 2020; Waltman, van Eck, & Noyons, 2010). Each cluster had authors who produced at least one research article and collaborated multiple times (Palmblad & van Eck, 2018).

Co-citation analysis (Marshakova, 1973; Small, 1973) was conducted to investigate the structures and research themes of the co-cited publications. Using CiteSpace version 5.1.R2 (Chen, 2017), the clusters’ themes were named based on the keywords designated by the authors of the collected articles and the WoS. The size of each cluster was proportional to the number of co-authored publications. The year of the creation of each cluster was when the first co-citation occurred.

“Comunicar” (108 times) was the journal where research articles on digital literacy were published most frequently (Table 1). This journal published over 1,770 articles on educommunication (education and communication) and ICT over the past 25 years (Comunicar, 2018). Other journals on the list were related to literacy (e.g. “Journal of Adolescent and Adult Literacy,” “Literacy”) and information, media, computers, and technology (e.g. “Computers and Education,” “Learning Media and Technology”). Journals that converse about science, nursing, health, and English education were also listed.

The frequent author keywords covered literacy, information and technology, pedagogy, student behavior, attitude, and beliefs (Table 2). “Media literacy” was the most frequent, and its plural form, “media literacies,” was also listed. Other keywords, such as “children,” “higher education,” and “teacher education,” narrated educational levels and age.

The most frequent topic keyword was “education” (Table 3). Some keywords were related to subjects at various ages (e.g. “students,” “children,” “adolescents”) and information and technology (e.g. “technology,” “Internet,” “Web,” “online”). Other research topics of the retrieved articles incorporated teaching and learning, curriculum, and learners’ attitude, belief, and behavior.

The co-occurring keywords included “information literacy,” “education,” “digital literacy,” “media literacy,” and “media literacies” (Table 4). Other co-occurring keywords were related to pedagogy (e.g. “instructional strategies,” “methods”), learners (e.g. “students,” “adolescence,” “university students,” “early adolescence”), Internet and technology (e.g. “digital,” “specific media”), and culture and literacy (e.g. “film,” “music,” and “popular culture”).

The co-occurring keywords were classified into seven clusters (Figure 1). Cluster 1 had the most keywords (78 keywords), while cluster 7 had the least keywords (12 keywords). More specifically, cluster 1 had keywords about digital literacy, learners’ attitudes, and learning contexts. Cluster 2 illustrated media and technology. It also talked about learners’ age group, learning strategies, teacher education, and health and social issues. Cluster 3 covered strategies for teaching and learning, research methods and fields, and learners’ age group. Cluster 4 discussed more diverse learner groups, including “university students” along with “writing,” “motivation,” “engagement,” “domain knowledge,” and “instructional strategies.” Cluster 5 had domain-specific terms that were mentioned with learners’ age groups and learning strategies. For instance, “chemical information,” “chemoinformatics,” and “organic chemistry” appeared with learner groups and learning strategic terms. Next, cluster 6 discussed culture and language, along with “multiliteracies,” “multimodality,” “policy,” and “reading.” Lastly, cluster 7 covered “assessment,” “credibility,” “epistemological beliefs,” “personal epistemology,” “prior knowledge,” and “comprehension” (see Appendix for the whole list of the co-occurring keywords). To sum, the range of research topics in digital literacy has been expanded, which embraces assessment, credibility, learners’ attitudes, and media literacy education. Learners, or study subjects, included from early adolescents to adults and professional groups, along with further clarifications by gender and identity.

Figure 1

The results revealed that 1,453 authors collaborated with other authors to write research articles. Table 5 shows the top co-authors by the frequency of co-authorship. Consequently, Valcke, M., Claro, M., and San Martin, E., respectively, produced research articles with other researchers the most. Valcke, M. studied innovation in higher education and the integrated use of ICT at Ghent University in Belgium (Ghent University, 2018). Claro, M. and San Martin, E. researched digital technology and education (Pontificia Universidad Católica de Chile, 2018).

The network of co-authors consists of 563 clusters. Of the total clusters, the top 10 clusters consisted of the most co-authors, respectively, and are presented in the current paper (Figure 2). In cluster 1, Han and Schuurmans-Stekhoven (2017) examined Asian students’ research literacy in higher education in Australia, using information and technology. Other co-author groups studied individual- and school-level variables which influenced South Korean primary students’ ICT literacy (Kim, Kil, & Shin, 2014) and South Korean secondary school students’ ICT literacy skills (Kim & Lee, 2013).

Figure 2

Next, in cluster 2, research on students’ use of iPad applications to obtain scientific knowledge and ask inquiries when they visited a science museum (Marty et al., 2013). Cluster 3 had a study on Brazilian students’ online use and their home background (Cabello-hutt, Cabello, & Claro, 2017). On the one hand, many of the authors found in cluster 4 worked together for Taiwanese primary school students’ ICT literacy improvement and learning-assistance tool (Huang et al., 2010). In cluster 5, a study on the perception of students at 20 secondary schools in Belgium for their use of video games in class (Bourgonjon et al., 2010). In cluster 6, literacy studies in health were found—the influence of anti-smoking media literacy curriculum for 1,170 9^th Grade American students’ media literacy and smoking (Primack et al., 2014) and online anti-smoking program for 9^th Grade students (Phelps-Tschang et al., 2015; Primack et al., 2009). Cluster 7 had research on students’ ICT literacy assessment instrument (Siddiq, Gochyyev, & Wilson, 2017), use of data for sustainable improvement of learning (Scalise & Wilson, 2011), and relationships between self-efficacy, ICT use, socio-economic background of about 60,000 students in 21 different countries located in Europe, Asia, and South America (Hatlevik et al., 2018). In cluster 9, Prieto et al. (2016) introduced four research projects on the socio-cultural approach to mobile learning. Another relevant article (Garcia et al., 2015) discussed the critical literacy of secondary school students, teachers, professors, and graduate students who were involved in the community for improving education in urban areas of the United States. Lastly, in cluster 10, the influence of emotional design in multimedia learning on understanding and achievement was studied (Plass et al., 2014). The authors of this study collaborated with other researchers to investigate how playing digital games accompanied by physical activity influences children’s reading skills between the ages of five and seven (Homer et al., 2014).

The co-authorship clusters showed how authors from certain countries collaborated (Figure 2). For example, cluster 1 was constructed by the co-authors from South Korea and Australia. Most researchers in cluster 4 were from Chinese taiwan. Other large clusters were shaped by American authors who worked with researchers from South America (e.g. Chile) and Europe (e.g. Norway, Germany, Finland, Belgium).

Table 6 shows the frequently cited journal articles, books, and reports. The books and chapters on the list discussed cultural competencies and social skills that are needed to exploit digital technology. Specific topics were sociocultural perspectives during the process of reading, writing, and deriving meaning (Jenkins, 2006a; Knobel & Lankshear, 2006), the change in media education (Buckingham, 2003), research methodology and literacy (Coiro et al., 2008), and literacy in New Media Age and Digital Age (Binkley et al., 2012; Fraillon et al., 2014; Kress, 2003). Of them, the most cited publication was Confronting the Challenges of Participatory Culture (Jenkins, 2006a, 2009), which was published as an occasional paper in 2006 and as a book in 2009.

Of the list, the frequently cited journal articles presented the results of experimental studies (Tables 6 & 7). Primarily, there were studies on learning outcomes and skills for digital literacy of the digital native who grew with using digital technology in their daily life (Bennett, 2008; Claro et al., 2012; Greene, Yu, & Copeland, 2014; Hargittai, 2010; Ng, 2012). Other studies presented educational programs for students in chemistry to master their literature searching skills (Gawalt & Adams, 2011; Locknar et al., 2012) and definition of media literacy, information literacy, and digital literacy (Koltay, 2011).

The co-cited publications were classified into eight clusters that described overarching topics (Table 8). The cluster numbers shown in Table 8 were designated by the analysis tool in accordance with the size of the cluster in ascending order. For example, cluster 0 has the most co-cited publications. That is, the biggest cluster was “digital literacy.” Other clusters included “ICT literacy,” “epistemic perspective,” “exploratory study,” “performance test,” “school-performance feedback use,” and “online forum.” Meanwhile, the visualized network of the clusters showed that the cluster, “integrating chemical information instruction,” was remote from the other clusters (Figure 3). This finding indicates that publications in “integrating chemical information instruction” were co-cited within the cluster, while publications in the other clusters were likely to be co-cited across the clusters.

Figure 3

A zoomed-in network of the clusters showed the co-cited publications between the clusters more precisely. Cluster color demonstrated a year when first co-citation occurred in a cluster (Chen, 2006), which means the time when the cluster was created. Yellow-green had its first co-citation in 2005, while co-citation occurred in more recent years as a cluster's color gets closer to red-orange. In terms of the two clusters with the same topic, “ICT literacy,” one was created in 2010, while the other one was in 2015 and is located between “Neil Postmans view” and “digital literacy” clusters in the network. “Digital literacy” clusters were adjacent to “performance,” and “exploratory study” and were closely related to “epistemic perspective” among the co-cited publications.