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Information literacy is a core research topic in the field of library and information science. The developmental context of this field can be examined through a long-term retrospective analysis of relevant literature. This study explored the research trends and potential research issues in the top 100 most frequently cited articles on information literacy in higher education published from 2011 to 2020. In addition to a systematic review, this study employed bibliometric methods, including co-citation network analysis, to identify four main research streams in the field of information literacy in higher education: (a) the relationships among students’ information literacy beliefs, competencies, attitudes and behaviour; (b) teachers’, librarians’ and students’ perspectives on information literacy; (c) the relationship between students’ information literacy and epistemic beliefs; and (d) the web search behaviour of digital natives. Accordingly, potential directions for future research and practitioner notes related to information literacy in higher education are proposed herein as a reference for researchers, teachers and policymakers. Implications for practice or policy: For administrators of higher educational institutions, understanding the challenges of new digital technologies and providing training to develop information literacy skills are crucial. For teachers, designing teaching materials and pedagogy based on the latest information literacy standards and framework is useful. Collaboration with professionals from different disciplines is also useful for teachers to integrate information literacy into subject learning activities to cultivate the information literacy competencies of students.

The main purpose of this study was to examine the critical factors influencing university teachers' use of a mobile technology-enhanced teaching (MTT) platform during the new coronavirus (COVID-19) epidemic. An integrated model with multiple factors drawing from the theoretical models and learning theories was proposed in this study to examine university teachers' intentions to use an MTT platform. The multiple factors included the individual factor (e.g., growth mindset, help seeking, and self-efficacy), the social factor (e.g., social norms), and the technological acceptance factor (e.g., perceived usefulness and perceived ease of use). The survey method was used to collect data on university teachers' perceptions of the MTT platform use, and a two-step structural equation modeling approach was used for the data analysis. Based on the path analysis of a total of 214 valid responses, the results identified that growth mindset, help seeking, and self-efficacy from the individual factor, as well as perceived usefulness from the technology acceptance factor were the significant determinants of university teachers' intentions to adopt the MTT. The contributions of this study are twofold. First, the proposed model was derived from multiple literature sources, providing a sound theoretical foundation to understand MTT platform use from an academic angle. Second, university teachers' viewpoints are a unique observation of their actual platform use, providing practical insights into the improvement and maintenance of MTT-related platforms for all educators. The findings are especially valuable during the post-COVID-19 era.

Programming learning has become an essential literacy for computer science (CS) and non-CS students in the digital age. Researchers have addressed that students’ conceptions of learning influence their approaches to learning, and thus impact their learning outcomes. Therefore, we aimed to uncover students’ conceptions of programming learning (CoPL) and approaches to programming learning (APL), and analyzed the differences between CS and non-CS students. Phenomenographic analysis was adopted to analyze 31 college students (20 CS-related, and 11 not) from northern Taiwan. Results revealed six categories of CoPL hierarchically: 1. memorizing concepts, logic, and syntax, 2. computing and practicing programming writing, 3. expressing programmers’ ideas and relieving pressure, 4. applying and understanding, 5. increasing one’s knowledge and improving one’s competence, and 6. seeing in a new way. Four categories of APL were also found, namely: 1. copying from the textbook, teachers, or others, 2. rote memory, 3. multiple exploration attempts, and 4. online or offline community interactions. Furthermore, we found that most CS students held higher level CoPL (e.g., seeing in a new way) than non-CS students. However, compared with non-CS students, CS students adopted more surface approaches to learning programming, such as copying and rote memory. Implications are discussed.

This study aims to identify research trends of scaffolding in the field of science education. To this end, both descriptive analysis and co-word analysis were conducted to examine the selected articles published in the Social Science Citation Index journals from 2000 to 2019. A total of 637 papers were retrieved as research samples through rounds of searching in Web of Science database. Overall, this study reveals a growing trend of science educators' academic publications about scaffolding in the recent two decades. In these sample papers, from 1,487 non-repeated keywords, we extracted 286 author-defined keywords shared by at least two studies as a benchmark dictionary. A series of co-word analyses were then conducted based on the dictionary to reveal the underlying co-occurring relationships of the words in title and abstract of the sample papers. Results showed that “scaffolding,” “support,” and “design” were the top three most frequently used keywords during 2000 and 2019. Visualization of co-word networks in each 5-year period further helps clarify both educators' common research foci and relevant research trends. Derived discussion and potential research directions are also provided.

This paper primarily aims to provide a citation-based method for exploring the scholarly network of artificial intelligence (AI)-related research in the information science (IS) domain, especially from Global North (GN) and Global South (GS) perspectives. Three research objectives were addressed, namely (1) the publication patterns in the field, (2) the most influential articles and researched keywords in the field, and (3) the visualization of the scholarly network between GN and GS researchers between the years 2010 and 2020. On the basis of the PRISMA statement, longitudinal research data were retrieved from the Web of Science and analyzed. Thirty-two AI-related keywords were used to retrieve relevant quality articles. Finally, 149 articles accompanying the follow-up 8838 citing articles were identified as eligible sources. A co-citation network analysis was adopted to scientifically visualize the intellectual structure of AI research in GN and GS networks. The results revealed that the United States, Australia, and the United Kingdom are the most productive GN countries; by contrast, China and India are the most productive GS countries. Next, the 10 most frequently co-cited AI research articles in the IS domain were identified. Third, the scholarly networks of AI research in the GN and GS areas were visualized. Between 2010 and 2015, GN researchers in the IS domain focused on applied research involving intelligent systems (e.g., decision support systems); between 2016 and 2020, GS researchers focused on big data applications (e.g., geospatial big data research). Both GN and GS researchers focused on technology adoption research (e.g., AI-related products and services) throughout the investigated period. Overall, this paper reveals the intellectual structure of the scholarly network on AI research and several applications in the IS literature. The findings provide research-based evidence for expanding global AI research.

PurposeThe purpose of this paper is to propose an innovative service model regarding the public library’s pilot project in Taiwan – Borrowing Books from Convenience Stores (BBCS). The proposed model presents a comprehensive evaluation of patrons to enhance readers’ intention to adopt this innovative library service.Design/methodology/approachA structured questionnaire was used to collect data from the users of the public library and convenience stores in Taiwan. Structural equation modeling was used to analyze the data.FindingsThe main findings of this study make both theoretical and practical contributions. First, this study explores the library’s extending service to convenience stores, and proposes an integrated BBCS model for the library’s innovative service. Second, the identification of influential factors, such as control influence, social interaction and perceived values of convenience, contributes to a marketing strategy for this innovative service offered by the library. Third, gender differences in some relationships of influential factors on BBCS use intention were identified.Originality/valueAlthough many studies have investigated the adoption of self-service technology, this paper is the very first attempt to explore the use of the innovative library service in convenience stores. Based on several theories, an integrated model for users’ intention to use BBCS is proposed in this study. The authors also recommend various gender-specific strategies of BBCS service.

This paper aims to provide a comprehensive analysis of publication patterns on computational thinking (CT) over two recent periods (period I: 2006–2012; period II: 2013–2018). Based on keyword analysis, a total of 3798 (period I) and 7175 (period II) keywords were found. Derived from the content analysis, a research typology of two-period keywords was consolidated and framed according to its attributes, including background settings, domain-specific factors, and learning outcomes. Main findings show as follows: (1) Regarding the research background, students from secondary and higher education are the main participants; and computer science, mathematics, and engineering are the major subjects. (2) As the domain-specific factors, game and peer collaboration were found to be the main pedagogies, while web-based and face-to-face learning environments were almost equally referred to in CT research settings. However, compared with traditional command-based tools, Scratch, Lego, and Python were identified as the emerging visual-based programming languages. (3) Finally, the keywords related to learning outcomes were classified based on the Bloom’s framework of three learning domains. First, knowledge and mental understanding are the main goals in the cognitive domain; motivation and attitude are the main tasks in the affective domain; and social and communication skills are the central outcomes in the training of psychomotor ability. Further discussions and research directions are provided.

Aims To identify and analyze the 100 most cited articles on nursing student education (NSE) that were published in nursing journals. Background The citation frequency of an article indicates its scientific impact. Analyzing highly cited articles on NSE enabled researchers to identify mainstream research types and acquire relevant information and knowledge. Design A retrospective bibliometric analysis with co-citation network analysis. Data sources We searched for journal articles on NSE from the Web of Science, and analyzed the 100 most cited articles (date of search: June 3, 2020). Review methods The theme, article type, journal, country, source of institutional articles, and publication year were counted and analyzed. The citation relationships among the most 100 cited articles of NSE were calculated and visualized. Results Articles included in this study were mostly empirical quantitative studies with a cross-sectional design, and were published in international nursing journals between 2000 and 2020. Their authors were mostly from the United States and the United Kingdom. According to the co-citation network analysis, four main research directions were identified: workplace mental health, simulation learning, spiritual care, and medication administration. Conclusion Workplace mental health was the major research topic on NSE. This research topic has spanned two decades (2000–2020). These articles were mainly published in the Journal of Advanced Nursing and Nurse Education Today. Some recent research topics, such as simulation learning and spiritual care were also identified. Findings provide a fresh review of the highly cited NSE articles, including the visualization of the NSE network.

The emergence of networking has been viewed as a critical educational innovation. To highlight some innovations in educational networking (EN) research, this paper provides a bibliometric overview of international EN research from 2000 to 2018. Based on a keyword search, a total of 1005 journal articles with 13,803 citations were obtained. Through careful bibliometric analyses, three main results were concluded. (1) The growth of EN articles and authors was up by 1.5 times from the first decade (2000&ndash, 2009) to the current one (2010&ndash, 2018). (2) The most influential journals (over 300 citations) were identified. The research scope covers education technology, higher education, education policy, and even AIDS (acquired immune deficiency syndrome) education. (3) Based on some popular bibliometric indicators, the changes of research trends can be seen from the comparison of the main streams, which are identified from the most influential articles. Classification of the main research streams was presented, providing a typological understanding of the EN literature. In the first decade of research, the two articles which ranked first in terms of overall citations and average citations are Horvat et al. (2003) (232 times) and Coburn and Russell (2008) (17.6 times), respectively. In the last decade, the article by Roblyer et al. (2010) received both the highest number of citations (407) and average citations (45.2). Finally, the main ideas of highly-cited articles were categorized into three research streams. While the EN research of the earlier decade focused on interpersonal relationships, that of the recent decade emphasized on some innovative networking approaches, such as social media for learning, and network-based methodologies. Further discussions are provided.

The purpose of this study is to explore the willingness of consumers on using mobile payments through the Innovation Resistance Theory (IRT) and Technology Acceptance Model (TAM). The research subjects weretheTaiwan mobile payment users, distribute surveys by using purposive sampling method from online. A total of 430 surveys were issued, 363 valid surveys were collected and achieving84.41% effective response rate. Collected data were analyzed through the confirmatory factor analysis, structure equation model and descriptive statistics. The results of this study are as follows: The model of user's behavior intention on mobile payment by using TAM and IRT has good compatibility; Innovation Resistance has a significant negative impact on perceptual usefulness and perceived ease of use; Perceptual usefulness and perceived ease of use has a positive impact on the behavior intention; Perceptual barriers can effectively influence innovation resistance. This study found that the. mobile payment users are negatively impacted on Innovation Resistance. The TAM is positively affecting the subsequent behavior intention, it can establish a brand image and increase consumer confidence in mobile payments.

This study was to examine a structural model incorporating motivation, goal orientations, and exercise involvement. A total of 398 valid questionnaires, including 229 male and 169 female college students, were collected for data analyzed. The statistical mode uses the Partial Least Squares, (PLS) for linear structure mode (SEM) analysis. The results showed that motivation significantly positively affected goal orientation and exercise involvement; goal orientation significantly positively influence exercise involvement, and motivation can influence exercise involvement through goal orientation. In combination, the apps users' motivation directly or indirectly affect exercise involvement, which shows that the users' motivation plays an important key role in exercise involvement, both in management and theory. These results indicated that the motivation and goal orientation proposed in this study can be used as a measuring standard for the exercise involvement of college students. Based on the objectives of this study and the empirical results, practical recommendations were also provided to serve as references for the industry and future researchers.

The main purpose of this paper is to investigate the intellectual structure of the research on educational technology in science education (ETiSE) within the most recent years (2008–2013). Based on the criteria for educational technology research and the citation threshold for educational co-citation analysis, a total of 137 relevant ETiSE papers were identified from the International Journal of Science Education, the Journal of Research in Science Teaching, Science Education, and the Journal of Science Education and Technology. Then, a series of methodologies were performed to analyze all 137 source documents, including document co-citation analysis, social network analysis, and exploratory factor analysis. As a result, 454 co-citation ties were obtained and then graphically visualized with an undirected network, presenting a global structure of the current ETiSE research network. In addition, four major underlying intellectual subfields within the main component of the ETiSE network were extracted and named as: (1) technology-enhanced science inquiry, (2) simulation and visualization for understanding, (3) technology-enhanced chemistry learning, and (4) game-based science learning. The most influential co-citation pairs and cross-boundary phenomena were then analyzed and visualized in a co-citation network. This is the very first attempt to illuminate the core ideas underlying ETiSE research by integrating the co-citation method, factor analysis, and the networking visualization technique. The findings of this study provide a platform for scholarly discussion of the dissemination and research trends within the current ETiSE literature.

The issues of metacognitive scaffolding in science education (MSiSE) have become increasingly popular and important. Differing from previous content reviews, this study proposes a series of quantitative computer-based analyses by integrating document co-citation analysis, social network analysis, and exploratory factor analysis to explore the intellectual structure of the MSiSE literature (i.e. the relationships within and between subfields of MSiSE). Co-citation refers to any two articles that are jointly referenced in other articles. After the computation of co-citation analysis, 27 articles that have been co-cited at least once by follow-up studies as references were identified as the final set of core articles. The whole co-citation profile of 27 cores with the 434 links was then visualized in a network through social network analysis, representing an overview for the intellectual structure of core MSiSE studies. The most cross-referenced underpinnings in the network focused on adaptive scaffolding for self-regulated learning to enhance students’ conceptual understanding and on younger students’ metacognition in online science inquiry learning environments. Furthermore, two emerging topics in the network were identified through an exploratory factor analysis as “non-technological metacognitive scaffolding media,” and “behavior patterns & task analysis in technology-infused environments.” Overall, the study provides an innovative review method of scholarly communication in the MSiSE literature.

“Graying of the globe” is an increasing phenomenon worldwide, accompanied with the expanding healthcare costs of long-term care and hospitalization. To deal with this issue, previous medical literature has suggested that the ultimate success of telemedicine depends not only on the technology itself but also on users’ acceptance of the technology. Differing from past healthcare studies which focused on physicians’ viewpoints, the current study investigates the use intention of mobile healthcare devices from the perspectives of elderly people in Taiwan. Meanwhile, this study proposes a model of mobile healthcare technology acceptance, and provides a theoretical and empirical assessment including sociological, technological, and individual variables. To achieve the research purpose, elderly people in the community were invited to participate in the study, with 338 effective questionnaires eventually collected for analysis using the structural equation modeling technique. The empirical results support the inc...

Recent studies have highlighted that social commerce has become a new type of electronic commerce since consumers' shopping behavior is heavily influenced by social media (e.g., Facebook, Twitter), such as reading comments and feedback on products. It is important to note that the development of social commerce has caught the attention of business practitioners; moreover, it is also essential for researchers to probe into the existing research on the rapid growth of social commerce. As such, the aim of our research review is to identify the core research themes and trends in social commerce. To gain deep insights from the academic research, we present a network-based citation analysis, that is, a main path analysis, to analyze the knowledge dissemination within the social commerce literature. To construct a holistic review of the social commerce research, in this study, we performed multi-keyword queries to search for relevant articles in two major sources of high quality academic journals, namely the Sciences Citation Index (SCI) and the Social Sciences Citation Index (SSCI). The timespan covers original papers and the most up-to-date research. Accordingly, a total of 319 journal articles with 3,753 citations were obtained and used for the main path analysis. Based on the algorithm of the search path link count, the traversal count of knowledge flow within the social commerce research network was calculated. In addition, the result of the top 10 critical main paths (key-routes) was mapped in a directed network graph. This is the very first attempt to profile the most critical developmental trajectories of social commerce research. The pilot results can serve as a research-based platform for scholarly discussion.

This study aims to verify and propose a modified technology acceptance model (TAM) to understand the antecedents of e-textbook adoption among college students. An extended TAM is to investigate college students’ intention to adopt e-textbooks. Measurement items were drawn and modified from existing validated scales. After data were collected from college students in Taiwan, structural equation modelling was employed to examine and compare the proposed model with the original model. Moreover, two tests were conducted to determine the extent of common method variance in the current data. The empirical findings support the inclusion of perceived enjoyment in the TAM. The proposed model explained 43% of the variance in behavioural intention, but explained 71% of the variance in attitudes, suggesting an explication of how the different determinants influence college students’ adoption of e-textbooks. The significance of the chi-square difference between the two models indicates that our proposed model shows a better fit to the data than the TAM does. Besides, perceived enjoyment is a critical factor in the influence of attitudes towards the usage of e-textbooks. Perceived ease of use is more influential than perceived usefulness in the determination of attitudes.

This study aims to derive meaningful implications on the antecedents and consequence of consumers' satisfaction towards Apps usage. Both utilitarian and hedonic views are incorporated into the Technology Acceptance Model (TAM). Further discussions and results will be provided for theoretical and practical implications.

This study reviews the journal publications of artificial intelligence-supported online learning (AIoL) in the Web of Science (WOS) database from 1997 to 2019 taking into account the contributing countries/areas, leading journals, highly cited papers, authors, research areas, research topics, roles of AIoL, and adopted artificial intelligence (AI) algorithms. Results indicate that, from 1997 to 2009, AIoL research focused on the combination of intelligent tutoring systems and distance learning. In 2010–2014, AIoL research emphasized learner-oriented learning. In 2015–2019, learner-system interactions to facilitate personalized, adaptive, and collaborative learning became the main focus. “Intelligent tutoring systems” have played the most important role in AIoL, followed by “profiling and prediction,” and “adaptive systems with personalization.” Accordingly, the roles and research trends as well as several suggestions for future research in the field of AIoL are provided as a reference for researchers and policy makers.