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A co-citation network of young children's learning with technology.

Introduction

With the fast-developing technologies and prevalent technology use in everyday life, the issue of young children's learning with technology (YCLT) has become increasingly important (Plowman, Stephen, & McPake, 2010). The growing trend of YCLT has attracted researchers' attention to the need to review the contents of the YCLT literature. They have confirmed the effects of technology on various domains of young children's learning. For example, Blok, Oostdam, Otter, and Overmaat (2002) performed a meta-analysis to review 42 research articles regarding computer-assisted instruction in support of beginning reading instruction. These researchers found that computer-assisted instruction was generally effective in terms of facilitating children's beginning reading abilities. Lankshear and Knobel (2003) developed a four-quadrant framework to categorize 31 studies that adopted new technologies to support early childhood oral language and literacy development. In their work, most of the studies were assigned to the quadrant that used stand-alone technological devices to facilitate children's encoding and decoding skills. Yelland (2005) synthesized the literature on the use of computers in early childhood education from 1994 to 2004. Based on a qualitative review, she indicated that the use of computers is helpful for promoting young children's language, cognitive, and social development. Slavin and his colleagues (2009) presented an alternative meta-analytic review, called best-evidence synthesis, to investigate the effectiveness of reading programs for elementary students. In their review, technology-enhanced reading was found to be correlated with reading achievement.

Recently, Hsin, Li, and Tsai (2014) conducted a content analysis to investigate 87 empirical studies of young children's use of technology for learning. They concluded three factors influencing children's learning through technology, and identified "children's development of digital literacy" as the emerging trend. Despite the abundant information obtained from Hsin et al. (2014) and the other abovementioned reviews, how YCLT studies relate to each other is still unknown. Moreover, some important issues need to be explored: What are the most often cross-referenced research streams of YCLT? To what extent have these streams in the YCLT research network been extended by the follow-up papers? In addition, from the perspective of a large number of citers, what is the latent structure in the field of the main YCLT literature?

To answer the above research questions, this study presents a structural overview of the current YCLT research based on the analysis of large citation data. Two complementary methods were used to achieve the above purposes: document co-citation analysis (DCA) and social network analysis (SNA). First, co-citation analysis, known as a powerful computational analysis from the field of bibliometrics, is used to detect the most frequently referenced topics underlying the literature structure (Small, 1973). A highly co-cited pair indicates that the nature of these two research papers is highly correlated; thus, follow-up studies are most likely to cite them together. All these citing and cited papers together form an invisible research network around the same issue (Small, 1973). Therefore, with the use of DCA, researchers can identify the core research issues within YCLT research based on the bibliographic evidence. Next, embedded in graph layout, SNA is advantageous for profiling the complex co-citation matrix which is obtained from co-citation ties (or research pairs) of the literature network (Borgatti, Everette, & Freeman, 2002). Moreover, based on the measures of centrality, SNA can identify the most central papers within the focal network. For example, some critical bridging papers that connect different research streams can be identified with the measure of betweenness centrality (Freeman, 1979).

In sum, the current study goes beyond Hsin et al.'s (2014) descriptive overview to determine the closeness and relationships of the 87 articles based on two novel methods. Therefore, this study contributes a bibliographic insight into the review study and provides a visualization overview of the contemporary YCLT literature.

Methods

Document co-citation analysis

The most important step for co-citation analysis is the collection of research data. Based on Hsin et al.'s (2014) research review on the influence of young children's use of technology for learning, a total of 87 empirical articles on YCLT were identified as candidate papers for this study. Accordingly, the first step of the analysis was to retrieve the bibliographic citation data of these 87 core documents from the Web of Science (WoS).

In line with the quality of these 87 journal papers, only journal citations were counted. For example, Clements and Sarama's research (2007) is the most highly cited paper among the 87 core papers, as it has been cited by 47 other journal articles (11 citations from book chapters and conference proceedings were excluded). Then, all of these 47 citing papers were retrieved from the WoS and the 47 citation counts were accredited to the work of Clements and Sarama (2007). By adopting the selection criteria of the citation data, a pool of 87 core papers together with all 560 citing articles were collected from the WoS. Overall, there are over 200 journals in this dataset, indicating the diverse nature of YCLT research. The data retrieval was performed on October 30, 2014.

Next, a series of computation analyses for constructing the co-citation matrix were processed. Specifically, all of the above 87 core papers were paired document by document, and then the co-citation counts for each research pair were calculated by matching the reference records within the 560 articles. According to Small (1973), when a pair of core studies (i.e., two of the 87 core papers) is referenced in the same citing article (i.e., 560 follow-ups), the frequency of co-citation for that research pair is then reckoned as one. For example, two highly cited YCLT papers, Clements and Sarama (2007; 2008), have been cited 47 and 28 times, among which, 10 follow-up studies have co-cited the two works. Endorsed by these 10 citing papers, the value of co-citation for this research pair (Clements & Sarama, 2007, 2008) in the co-citation matrix is input as 10. Likewise, the co-citation relationships among all the research pairs of the 87 core YCLT papers were calculated based on the large citation data from the 560 follow-up references. Among the 87 papers, however, 34 which have not yet been co-cited by any other YCLT studies were excluded because papers without co-citation were not able to create a co-citation linkage on the co-citation map. Note that most of these excluded papers (24 out of 34) were published after 2010, and thus have less chance of having co-citation relationships with other core YCLT papers. The computation results for the remaining 53 papers were then compiled into a symmetric co-citation matrix of 53 rows and 53 columns. The full list of 53 core papers is available at: http://goo.gl/XLJuqq.

Social network analysis

In recent educational review studies, social network analysis (SNA) is a relatively novel technique for visualizing results; using this technique, one can more easily understand the research network of the most prominent studies (Tang, Tsai, & Lin, 2014; Tang & Tsai, 2016). The visible network displays the academic interactions in the bibliometric contexts like a scholarly communication of invisible colleagues (i.e., the co-citation network) that previous researchers may be unaware of themselves. Therefore, the use of SNA in this review permits the exploration of existing linkages among 53 YCLT articles.

Furthermore, three measures of centrality (i.e., the degree, closeness, and betweenness centralities) were also adopted to profile the centrality features of the most central works in the YCLT co-citation network. The degree centrality is the most straightforward measure of the connectedness of each node (which is the label for a core paper presented on the graph). The closeness measures nodes' independence (i.e., less connectedness); therefore, the more central role a node plays, the less closeness centrality it has. The betweenness centrality is the index reflecting the bridging role of a node in the network; the more critical bridging role a node plays, the more strongly it controls the communication between sub-networks (called a "broker") (Freeman, 1979). In this study, the measure of degree centrality is presented as the amount of connectedness which a node has. The closeness and betweenness centralities are presented as normalized measures based on Freeman's (1979) approach.

Results

Results of the document co-citation analysis

Through matching the reference data within 560 citing articles, a total of 206 co-citation ties within 53 core papers were found in the co-citation matrix. The higher the correlation between research pairs, the more bibliographical similarity they will have. In the co-citation matrix, the highest co-cited research pair is composed of two studies by Shimizu and McDonough (2006) and Donker and Reitsma (2007). The two studies are related to the use of a computer mouse by young children and have been co-cited 14 times. In Shimizu and McDonough (2006), they taught three four-year-olds with a developmental delay the skill of pointing with a computer mouse. The children learned pointing after receiving instructional prompts. In Donker and Reitsma (2007), they investigated the efficiency of two ways of moving objects over the screen, drag-and-drop and click-move-click. They found dragand-drop more efficient for young children.

Another highly co-cited pair consists of two studies by Clements and Sarama in 2007 and 2008 (co-cited 10 times), which focused on the evaluation of a research-based mathematics curriculum, Building Blocks, for preschoolers of low-income families. The curriculum integrated computer and off-computer activities and included three types of materials: computer software, manipulatives, and printed materials. In 2007, they used a quasi-experimental design and implemented the curriculum in four classrooms; in 2008, they then adopted an experimental design and expanded the participants to 36 classrooms. Both studies showed that the children improved their mathematics performances after attending the intervention program.

The remaining three highly co-cited pairs are closely tied with each other as a triangle as shown in Figure 1. Of these, the first pair is composed of the studies by De Jong and Bus (2004) and Chera and Wood (2003), which received the most co-citations, numbering 11. Moreover, these two studies are both tied with Segers, Takke, and Verhoeven's (2004) article, forming the remaining two highly co-cited pairs. The topic of the three cross-linked studies is the effectiveness of electronic books for young children's literacy development. Chera and Wood (2003) investigated the effect of e-books on the development of phonological awareness of 3-6-year-olds in comparison with children who did not read an e-book. They found that children who read e-books improved their phonological awareness. Sharing the same research question, the research of De Jong and Bus (2004) and Segers et al. (2004) compared the effects of children's reading of e-books independently with the effects of children being read to by an adult. The results revealed that children's comprehension of the stories and vocabulary learning were similar in the two reading conditions--being read to by a computer or by an adult.

Overall, the co-citation analysis has identified five highly referenced YCLT research pairs, which have a tight connection and a high similarity with each other. From the large citers' perspective, these five research pairs provide the research foci of the current YCLT literature, including the use of a computer mouse by children, a children's technology-assisted mathematics curriculum, and the effect of e-books on children's literacy development. It is noteworthy that although these three research topics with high co-citation numbers may indicate that they are the most influential core works of YCLT, the analysis of their follow-up studies revealed that they are immature and have not yet been fully explored.

Results of the social network analysis

To further illuminate the configuration of the research network of the 53 YCLT papers, social network analysis was conducted to visualize all of the co-citation ties in the co-citation network. By using the NetDraw module of UCINET (Borgatti et al., 2002), the layout of the 53 research works was denoted as 53 nodes, and every co-citation tie was a link between each pair of nodes. The thickness of the co-citation links stands for the weights of the different co-citation ties.

[FIGURE 1 OMITTED]

As a result, the three most highly referenced ties, which have been co-cited over 10 times, are highlighted as strong ties and are presented as three red solid edges in the diagram. The other two blue lines represent moderate ties, which have been co-cited 5 times. While those edges which received the strength of ties ranging from 2 to 4 are presented as black solid lines, the rest of the ties with minimal co-citation linkages are marked as gray lines. As shown in Figure 1, the whole structure of the YCLT co-citation network can be divided into two sectors: (1) the main component (in the center), and (2) the isolated components (on the upper-right side). The structural relationships among the nodes are further explored according to the research purposes and learning domains of the 53 studies.

Overall, seven research streams are identified. Three major research streams are acknowledged in the main component of the network (i.e., technology-assisted language learning, digital literacy, and technology competence) and the other four (relatively marginal) streams (including mathematical learning with technology, social interaction through technology, video-enhanced learning for autistic children, and technology as learning companion) are mapped into the isolated components. A summary is presented in Table 1.

Main component of the co-citation network

The main component of the YCLT network consists of 42 YCLT papers, representing the major YCLT research community. Studies included in this component are well connected and are covered by three research streams: (1) technology-assisted language learning, (2) digital literacy, and (3) technology competence.

Graphically, "technology-assisted language learning" constitutes the largest area of the main component and includes 29 papers, indicating that it is the most researched stream in the currently reviewed YCLT studies. In addition, this research stream has received the highest numbers of citations and co-citations, signifying the emphasis on language learning in YCLT research. Moreover, the papers of "technology-assisted language learning" are published between 2003 and 2012, that is, right across the time period of this review. This indicates that the use of technology to support language learning is a longstanding and continuing research stream. While most papers in this stream were to compare the effects of technology-assisted learning and the traditional method, some studies focused on the effects of different pedagogical or mechanical designs, and the mediator-roles of adults.

Electronic books (e-books) and computer programs were generally implemented to facilitate young children's language learning. For example, Helland, Tjus, Hovden, Ofte, and Heimann (2011) examined the effectiveness of different computer-based training programs on children with developing dyslexia. They found that bottom-up training (i.e., from sound to meaning) is appropriate for young children's pre-literacy skills, such as phonological awareness, and top-down training (i.e., from meaning to sound) has a significant effect on promoting literacy skills, such as word reading and spelling. On the other hand, the use of e-books (e.g., animated multimedia talking books) was found to have significant effects on promoting young children's phonological awareness (Chera & Wood, 2003). Therefore, there are two sub-networks distinguished by the types of technology adopted to support learning, that is, "e-books" and "computer programs."

Most research nodes of "e-books" are connected in the right area of the co-citation network. This research sub-stream includes 4 highly cited papers (i.e., cited more than 10 times) and 7 more recently published works. The former three of four highly cited papers (Chera & Wood, 2003; De Jong & Bus, 2004; Segers et al., 2004), which link as a triangle-shaped tie in this sub-stream, provide a key foundation for the research network of e-book related studies. Overall, the high average number of co-citations (11.7) also implies frequent interactions in this community.

The other sub-stream of language research consists of 15 studies that implemented computer programs to facilitate children's learning of literacy. The network connection in computer programs research (7.9) is less tight than it is in e-books (11.7). Although five papers are cited more than 10 times, no strong or moderate co-citation ties are found in this sub-stream. Two computer programs were highlighted: while some researchers investigated the effectiveness of a technology-rich curriculum, named PictoPal, in terms of promoting emergent literacy, the others evaluated a web-based tool, Abracadabra, designed for supporting reading.

The second research stream derived from the main component is "digital literacy." This stream comprises 10 studies emphasizing young children's digital literacy by (1) exploring the associations between children's technology experience in daily life and their development; and (2) investigating children's access and use of computers outside schools and informing educators of the importance of taking children's technological abilities and experience into account when arranging appropriate learning environments and experiences for young children. Most of the papers in this research stream were published after 2011. Compared to studies of language learning, "digital literacy" is a relatively new and emerging research stream that has started to draw attention from researchers during recent years.

The third research stream is labeled as "technology competence" and includes only three papers. Donker and Reitsma (2007) and Shimizu and McDonough (2006) are the most highly co-cited YCLT works in the current review and represent this research stream. These two works, which are cross-referenced as many as 14 times, investigated children's use of the computer mouse. The other study was conducted by Romeo and his colleagues (2003) to explore children's interactions with touchscreens.

Isolated components of the co-citation network

Compared with the main component of the network, the co-citation relationships in the isolated components are relatively loose, with only 4.7 co-citation counts on average. Four isolated components are located in the upper right corner of Figure 1, each representing a small research stream: (1) mathematical learning with technology, (2) social interaction through technology, (3) video-enhanced learning for autistic children, and (4) technology as a learning companion.

Although shown as marginal research streams, they include the top four highly cited papers of all the reviewed YCLT studies: Clements and Sarama (2007) (47 citations), Cihak, Fahrenkrog, Ayres, and Smith (2010) (41 citations), Ryokai, Vaucelle, and Cassell (2003) (28 citations), and Clements and Sarama (2008) (28 citations). The importance of these isolated research streams represented by the four leading papers cannot be overlooked.

Two highly cited works of Clements and Sarama (2007, 2008) represent the research stream of "mathematical learning with technology." In these two works, a computer-supported math curriculum (Building Blocks) was adopted to promote the concepts of numbers and geometry. The average co-citation of this research stream is the highest among the four isolated papers. This indicates that the papers in this stream are often cross-referenced and are highly recognized, even though this research community is very small and not part of the main research stream.

"Social interaction through technology" is the most up-to-date research stream in the YCLT network that is under development. The studies were published between 2010 and 2012 and started to discuss the roles of social interaction (including adult-child or child-child interactions) in supporting children's learning during technology use. Two frequently co-cited works (Plowman et al., 2010; Wolfe & Flewitt, 2010) both employed the sociocultural approach to discuss the importance of adults' roles in children's use of technology and how adult-child interaction facilitates children's literacy learning, computer competence skills, understanding of the cultural role of technologies, and communication with family members.

The other two smallest research streams both consist of two studies. In "video-enhanced learning for autistic children," Dauphin, Kinney, and Stromer (2004) employed video-enhanced activity training to teach play and communication skills to a child with autism. Cihak et al. (2010) adopted video modeling to improve transitional behaviors for young students with autism. The last research stream identified in the isolated components is "technology as learning companion." Ryokai et al. (2003) created a virtual peer to interact with children in a storytelling activity to facilitate their literacy learning. Luckin, Connolly, Plowman, and Airey (2003) employed digital toys and the associated software and investigated children's interactions with the technologies. These two streams are the least active research community of the YCLT studies.

Central papers in the co-citation network

In addition to the angle of classification for the research network of YCLT, three measures of centrality were used to identify the most central papers in the network. Accordingly, the most central papers in terms of the role of centrality are the works of Chera and Wood (2003), Levy (2009), Lonigan et al. (2003), Magnan and Ecalle (2006), Segers et al. (2004), and Segers and Verhoeven (2005).

Among the six central papers, the most critical paper in the overall YCLT research network is Levy (2009). This paper has the highest degree of centrality and betweenness centrality showing that it not only connects to the largest number of YCLT studies, but also plays an important role of broker in the network. Besides, its closeness centrality is also listed as the second highest, indicating its close relationship with other studies of the YCLT research. In Figure 1, Levy's work is connected to 12 studies including 7 in "digital literacy" and 5 in "technology-assisted language learning." This suggests the close connection between Levy's paper and the two main research streams.

Levy's (2009) role of broker in two research streams can be further revealed from the research emphasis of the study. In Levy's work, she investigated the influences of how schools teach children to read print texts on their ability to read multimodal texts. She found that children had developed the ability to read multimodal texts (digital literacy) at home by holistic understanding rather than by decoding the texts. However, when they learned decoding texts in school, their confidence in reading multimodal texts diminished. While researchers have emphasized the effectiveness of using computer programs or e-books to promote children's particular language abilities, Levy's study started a new direction for exploring the association between children's technology use and their development of literacy and digital literacy.

Other than Levy's (2009) work, the other five papers are core papers in the stream of "technology-assisted language learning." These studies are targeted mainly on the facilitation of phonological skills and vocabulary learning. Two central works on "e-book" studies were conducted by Chera and Wood (2003) and Segers et al. (2004). These two studies compared the effects of using e-books to promote language learning with general instruction activities or teacher-mediated storybook reading. The other three studies implemented computer programs (including computer games) to enhance the phonological skills of children with reading disadvantages (e.g., Lonigan et al., 2003). Moreover, the nodes of Lonigan et al. (2003) and Chera and Wood (2003) adopted technology to improve children's phonological awareness, and seem to represent the beginning of two sub-streams of research in language learning.

Discussion

In this section, we begin with a discussion of the two major findings in terms of the five major co-citation pairs and of the overall YCLT co-citation network. In addition, a comparison between two different methods of content and co-citation network analysis is also provided. Some methodological remarks regarding the use of co-citation network analysis are also suggested for future review studies.

Five major co-citation pairs in the YCLT research network: exploration and extension

As seen in Figure 1, five major pairs of research in the YCLT research network were identified. Among them, the highest co-cited studies (i.e., Shimizu & McDonough, 2006; Donker & Reitsma, 2007) are related to the use of the computer mouse by young children. To understand how this topic has developed over time, we further examined 14 studies which co-cited this research pair. Most studies (13 out of 14) were from Shih and his colleagues (e.g., Shih, Shih, & Peng, 2011). Their series of studies focused on evaluating disabled persons' pointing performances (including children and adults with disabilities) after using various evolving programs which were developed to improve their pointing skill. Their studies also found that young children's use of the computer mouse is related to the development of digital literacy (some gray links tied with the areas of technology competence and digital literacy, Figure 1). For future study, researchers can conduct studies connecting digital literacy with other developmental domains for young children. For example, how the design of touch screens influences young children's scientific learning.

The second highly cross-referenced research pair (Clements & Sarama, 2007; 2008) is focused on the evaluation of a mathematics curriculum, Building Blocks. After examining the pairs of follow-up references, we found that 5 out of 10 follow-up papers modified the original curriculum and explored the relationships between the performances of mathematics and literacy as well as oral language (Clements & Sarama, 2011a; Clements et al., 2011b; Clements et al., 2013; Sarama, Clements, Wolfe, & Spitler, 2012; Sarama, Lange, Clements, & Wolfe, 2012). However, only Clements, Sarama, and their colleagues have worked on the important topic regarding the role of technology-enhanced activities in children's learning of mathematics. Therefore, we suggest that future research can compare the effectiveness of (1) mathematics computer programs and off-computer activities, (2) mathematics computer programs developed on the basis of different pedagogical approaches, and (3) different types of technology (e.g., augmented reality, robots, computer games, electronic books, and online learning) in young children's learning of mathematics. Last, the topic of the relationship between young children's competencies of mathematics and other developmental domains or subjects (e.g., social development) needs further investigation.

The remaining three highly co-cited pairs in the main component of the network are tied with each other as a triangle (i.e., De Jong & Bus, 2004; Chera & Wood, 2003; Segers et al., 2004. see Figure 1). Their research topic is the effectiveness of electronic books in terms of young children's literacy development. Our co-citation analysis shows that 13 follow-up studies of the three pairs focused on the same issue among which eight studies, conducted by the research team of Korat, Shamir, and their colleagues, thoroughly explored the effects of e-books on emergent literacy. The remaining co-citing references include four empirical studies and one review paper. The topics of these articles all focus on how technology helps young children's literacy development. A close analysis of the empirical studies revealed that young children's e-book reading has been extended in three directions. First, Krcmar and Cingel (2014) turned their attention to adults' reading of storybooks, and examined the difference in young children's literacy growth between the reading of e-books and printed books. Second, Gong and Levy (2009) designed and implemented two kinds of e-books: a ball bouncing above a word when the word was read to increase children's awareness of the sound of each word, and unreadable words being inserted into sentences to draw children's attention to the components of readable words. Third, other types of technology rather than e-books were used to promote young children's emergent literacy, such as computer programs (Van der Kooy-Hofland, Bus, & Roskos, 2012) and videos (Strouse, O'Doherty, & Troseth, 2013). In conclusion, five research themes have emerged as future research directions, including: (1) the role of adults in children's reading of e-books, (2) the role of peers in coreading e-books, (3) the effective designs of e-books, (4) the effects of other types of technology on emergent literacy, and (5) the literacy gains of reading e-books for children of various developmental levels.

The co-citation network of 53 YCLT empirical studies: overview

Early childhood education is multidisciplinary and interdisciplinary. However, from the co-citation network, it is apparent that the YCLT research is dominated by studies of language learning and digital literacy. Other learning domains (e.g., math and social interaction) have, however, received far less attention from researchers and been isolated from the main streams (i.e., language learning and digital literacy). A gap seems to exist between the main research streams and the other smaller ones. In addition, it is apparent that the current YCLT research is domain specific rather than domain integrated. Technology has opened a way to integrate learning from different aspects. To bridge the gaps in the YCLT research, we suggest that more studies can adopt various technologies (e.g., augmented reality, robots, and interactive whiteboards) and utilize them to integrate different learning domains.

In addition, the co-citation network of YCLT suggests that digital literacy appears as an important emerging stream. Our results also reveal a close connection between "digital literacy" and "technology-assisted language learning" in the YCLT network. This implies that researchers might consider digital literacy as an extension or an alternative form of literacy. "Technology competence" is naturally considered part of digital literacy; however, it is almost isolated from the network of "digital literacy." This might be due to the fact that the advances in technology (e.g., touch screen devices) have made the computer mouse less important. This notion is also confirmed by the above analysis of the follow-up citations.

Overall, digital literacy plays an important role in technology-assisted learning. Based on the results of the co-citation network, digital literacy is expected to have a close relationship with all of the other learning domains. Therefore, future research may explore how digital literacy is related to other learning domains for young children, and whether digital literacy can be assessed as general abilities required for learning or whether it can be demonstrated only through content or domain-dependent tasks. Compared with Hsin et al.'s (2014) conceptual analysis, ours provides further bibliographic evidence by co-citation network analysis to exhibit the current developments of digital literacy in the YCLT literature.

The use of co-citation network analysis for literature reviews

Content analysis has long been used as a typical method of literature review in education research. Most coding schemes for categorization used in content analysis are based on researchers' deductive observations or on an a priori framework of past studies. For example, Hsin et al. (2014) proposed a typology based on the content analysis of five categories, and indicated some key factors influencing children's learning through technology. In this present study, we take a distinct viewpoint by integrating co-citation analysis and social network analysis to examine the YCLT literature using their cited references.

First, the co-citation analysis provides abundant citation-based evidence to determine the closeness and relationships among the core papers. Based on the view of a large number of citers, therefore, the results can identify some bibliographically-related documents and group them into individual research streams. Second, the technique of networking visualization presents a clear structural overview of the literature, delivering a fresher review methodology. Some central cores and most referenced research sub-fields can be directly observed in the research network. Overall, the integrative approach of co-citation network analysis in this study offers researchers a relational overview of the core papers, and a structural understanding of the YCLT research network which reflects a field's view of itself. This study is especially significant because, for instance, based on the results, researchers who are very new to the YCLT area can start by reading some focal research papers. On the other hand, senior scholars may conduct some interdisciplinary studies to connect different research topics.

For future studies, researchers can use co-citation network analysis to explore the relationships among other research topics in education or in any scientific research areas. Some statistical methods (e.g., factor analysis or cluster analysis) are suggested to integrate with co-citation analysis to quantitatively classify documents into different research groups. Furthermore, other co-citation analyses (e.g., author co-citation or journal co-citation analyses) can be adopted to provide different views of a discipline.

Conclusion and limitations

Overall, this paper contributes to the literature in a number of ways: it provides a fresh approach to research review and presents a critical content-based discussion based on the results of network analysis. The application of cocitation network analysis also provides a new research model for exploring research domains in other scientific disciplines.

Two limitations are, however, noted. First, the research network presented in this study is a citation-based result. Although highly co-cited pairs are endorsed by large citation data, some false citations in the publication may not be detected by co-citation network analysis. A further extensive content analysis is suggested to examine in more depth the relationships of citation and co-citation among the core papers. In addition, only journal papers were included in this study. Future research may consider other sources, such as conference proceeding papers, to quickly track the contemporary research trends. Last, the co-citation network is dynamic as the citation data changes daily. Researchers may include new citation data and newly published papers to analyze the YCLT research network. Bearing these limitations in mind, this study presents the overall intellectual structure of YCLT for further scholarly discussion.

Acknowledgments

This research is partially supported by the Ministry of Science and Technology, Taiwan, under Grant number MOST 101-2511-S-011-003-MY3, 104-2517-S-011-001 -MY3, and MOST 104-2511-S-011-004-MY3.

References

The core papers are preceded by an asterisk (*).

Blok, H., Oostdam, R., Otter, M. E., & Overmaat, M. (2002). Computer-assisted instruction in support of beginning reading instruction: A Review. Review of Educational Research, 72(1), 101-130.

Borgatti, S. P., Everette, M. G, & Freeman L. C. (2002). UCINET for Windows: Software for Social Network Analysis. Harvard, MA: Analytic Technologies.

* Chera, P., & Wood, C. (2003). Animated multimedia "talking books" can promote phonological awareness in children beginning to read. Learning and Instruction, 13(1), 33-52.

* Cihak, D., Fahrenkrog, C., Ayres, K. M., & Smith, C. (2010). The Use of video modeling via a video iPod and a system of least prompts to improve transitional behaviors for students with autism spectrum disorders in the general education classroom. Journal of Positive Behavior Interventions, 12(2), 103-115.

* Clements, D. H., & Sarama, J. (2007). Effects of a preschool mathematics curriculum: Summative research on the building blocks project. Journal for Research in Mathematics Education, 38(2), 136-163.

* Clements, D. H., & Sarama, J. (2008). Experimental evaluation of the effects of a research-based preschool mathematics curriculum. American Educational Research Journal, 45(2), 443-494.

Clements, D. H., & Sarama, J. (2011a). Early childhood mathematics intervention. Science, 333(6045), 968-970.

Clements, D. H., Sarama, J., Spitler, M. E., Lange, A. A., & Wolfe, C. B. (2011b). Mathematics learned by young children in an intervention based on learning trajectories: A Large-scale cluster randomized trial. Journal for Research in Mathematics Education, 42(2), 127-166.

Clements, D. H., Sarama, J., Wolfe, C. B., & Spitler, M. E. (2013). Longitudinal evaluation of a scale-up model for teaching mathematics with trajectories and technologies: Persistence of effects in the third year. American Educational Research Journal, 50(4), 812-850.

* Dauphin, M., Kinney, E. M., & Stromer, R. (2004). Using video-enhanced activity schedules and matrix training to teach sociodramatic play to a child with autism. Journal of Positive Behavior Interventions, 6(4), 238-250.

* De Jong, M. T., & Bus, A. G (2004). The Efficacy of electronic books in fostering kindergarten children's emergent story understanding. Reading Research Quarterly, 39(4), 378-393.

* Donker, A., & Reitsma, P. (2007). Young children's ability to use a computer mouse. Computers & Education, 48(4), 602-617.

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Kai-Yu Tang (1), Ming-Chaun Li (2), Ching-Ting Hsin (3) and Chin-Chung Tsai (1) *

(1) Graduate Institute of Digital Learning and Education, National Taiwan University of Science and Technology, Taiwan // (2) Graduate Institute of Applied Science and Technology, National Taiwan University of Science and Technology, Taiwan // (3) Department of Early Childhood Education, National Hsinchu University of Education, Taiwan // ky.nctu@gmail.com // mliltw@gmail.com // cthsin@mail.nhcue.edu.tw // cctsai@mail.ntust.edu.tw

* Corresponding author

(Submitted May 3, 2015; Revised September 19, 2015; Accepted October 19, 2015)
Table 1. Summary: Research streams of YCLT research

Research          Papers   Main journals
streams

Technology-         29     Computers & Education (6)
assisted                   Reading and Writing (3)
language
learning

E-books             11     Computers & Education (3)
                           Reading and Writing (3)

Computer            15     Computers & Education (3)
programs                   Australasian Journal of
                           Educational Technology (2)
                           Journal of Computer
                           Assisted Learning (2)

Digital             10     English Teaching-Practice
literacy                   and Critique (2)
                           Computers & Education (2)

Technology          3      British Journal of
competence                 Educational Technology (1)
                           Computers & Education (1)
                           Research in Developmental
                           Disabilities (1)

Mathematical        4      American Educational
Learning with              Research Journal (1)
Technology                 Early Education and
                           Development (1)
                           Journal for Research in
                           Mathematics Education (1)
                           Learning and Instruction (1)

Social              3      Cambridge Journal of Education (1)
interaction                Computers & Education (1)
through                    Research Papers in Education (1)
technology

Video-enhanced      2      Journal of Positive Behavior
learning for               Interventions (2)
children with
autism

Technology as       2      Journal of Computer
learning                   Assisted Learning (2)
companion

Research            Active year      Total co-   Average co-
streams            (average year)    citations    citation
                                                 (per paper)

Technology-       2003-2012 (2008)      254          8.8
assisted
language
learning

E-books           2003-2012 (2008)      129         11.7

Computer          2003-2012 (2007)      119          7.9
programs

Digital           2008-2013 (2011)      46           4.6
literacy

Technology        2003-2007 (2005)      34          11.3
competence

Mathematical      2007-2013 (2009)      35          8.75
Learning with
Technology

Social            2010-2012 (2010)       9            3
interaction
through
technology

Video-enhanced    2004-2010 (2007)       2            1
learning for
children with
autism

Technology as     2003-2003 (2003)       6            3
learning
companion

Research            Total       Average      Average
streams           citations    citation      citation
                              (per paper)   (per year)

Technology-          292         10.1           45
assisted
language
learning

E-books              107          9.7          18.7

Computer             118          7.9          16.9
programs

Digital              37           3.7           12
literacy

Technology           47          15.7          5.4
competence

Mathematical         96           24           19.2
Learning with
Technology

Social               13           4.3          3.3
interaction
through
technology

Video-enhanced       68           34           9.7
learning for
children with
autism

Technology as        32           16           2.9
learning
companion
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Author:Tang, Kai-Yu; Li, Ming-Chaun; Hsin, Ching-Ting; Tsai, Chin-Chung
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Date:Jul 1, 2016
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