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MOOCs (massive open online courses) have attracted considerable attention from researchers. Fueled by constant change and developments in educational technology, the trends of MOOCs have varied greatly over the years. To detect and visualize the developments and changes in MOOC research, 4,652 articles published between 2009 and 2021 were retrieved from Web of Science and Scopus with the aid of CiteSpace. This study sought to explore the number of publications, co-citation network, cluster analysis, timeline analysis, burstness analysis, and dual-map overlays based on co-citation relationships. The first finding was that the number of publications on MOOCs had increased consistently, and grew especially quickly between 2013 and 2015. Second, the main topic of the top 10 co-cited studies revolved around the problem of learner continuance. Third, blended programs, task-technology fit, and comparative analysis have emerged as popular subjects. Fourth, the development of MOOC research has followed distinct phases, with 2009 to 2012 the starting phase, 2013 to 2015 the high growth phase, 2016 to 2018 the plateau phase, and 2019 to 2021 another peak phase. Lastly, both cluster analysis and dual-map overlays provided empirical evidence of cross-disciplinary research. Our findings provided an in-depth and dynamic understanding of the development and evolution of MOOC research and also proposed novel ideas for future studies.

Considering the importance of group member familiarity in collaborative learning in classroom learning environments, this study examined the impact of group member familiarity on CSCL (computer-supported collaborative learning) in a networked setting. Also, the differences between CSCL in the online environments and FtF (face-to-face) collaborative learning were also compared. An analysis using structural equation modeling revealed that group member familiarity increased teamwork satisfaction, which in turn increased student engagement and perceived knowledge construction. A multi-group analysis revealed that while FtF collaborative learning exhibits higher levels of group member familiarity, teamwork satisfaction, student engagement, and perceived knowledge construction, the mediating effect of teamwork satisfaction was more pronounced in online settings. The study findings provided insights for teachers to improve collaborative learning experiences and adapt different teaching strategies.

Prior research has explored the impact of diverse anthropomorphic interventions on the effectiveness of AI (artificial intelligence) instructors. However, the exploration of interpersonal communication skills (e.g., self-disclosure) as anthropomorphic conversational cues for AI instructors is rare. Considering the positive impact of the self-disclosure of human instructors and guided by the social penetration theory (Altman & Taylor, 1973) and computers are social actors (CASA) paradigm (Nass & Moon, 2000), this study explores the role of self-disclosure by AI instructors and the mediating role of emotional attachment between AI instructors' self-disclosure and students' learning experiences (learning interest and knowledge gain). Additionally, it examines the differences in students' emotional attachment, learning interest, and knowledge gain between AI and human instructors. Through a 2 (AI instructor vs. human instructor) × 2 (self-disclosure: yes or no) experiment, this study concluded that 1) consistent with human instructors, self-disclosure by AI instructors led to higher emotional attachment, learning interest, and knowledge gain; 2) emotional attachment played an important mediating role in AI instructor self-disclosure and students' learning interest and knowledge gain; and 3) in the context of self-disclosure, students exhibited similar levels of emotional attachment to both AI and human instructors, with no significant differences observed. Regarding learning outcomes, while students demonstrated a greater interest in learning during courses taught by AI instructors, the difference in knowledge gained from AI and human instructors was not significant. The results of this study contribute to the understanding of the anthropomorphic cues of AI instructors and provide recommendations and insights for the future use of AI instructors in educational settings. [ABSTRACT FROM AUTHOR]

It is important to examine how start-up innovation is emerging in the information society. The media is a window through which innovation is highlighted in which fields. We conducted a comparative study with North America to comparatively analyze how startup innovation in East Asia appeared. This study used a set of computer analysis methods including Dirichlet-multinomial regression Topic Model and Topic network analysis. News articles from 2000 to 2019 were collected from East Asia and North America and were analysed on the topic of start-ups. The results indicated that the discourse of start-ups from East Asia and North America in the 2000s and 2010s showed distinctly different trends. The East Asia media changed its focus from an innovation economy to an emerging industry: mobility & energy, while the North American media showed a change from revenue sources to the benefit of innovation. In the discourse of start-ups in East Asia, the government-centred innovative economy was emphasised in the 2000s, and expectations for emerging industries such as mobility and energy increased after the 2010s. Meanwhile, in the discourse of start-ups in North America, revenue sources were emphasised in the 2000s, and the proportion of beneficiaries of innovation increased after the 2010s. [ABSTRACT FROM AUTHOR]

To stay competitive, retail companies have introduced innovative retailing strategies for enhancing the consumer experience. Among these, omnichannel retailing services are one of the most critical services. However, studies on the loyalty required to secure the market using omnichannel strategies are limited. Instead of arbitrarily selecting key factors for users' loyalty based on previous research data used by users in social networking services were evaluated in this study, and the validity of the selection of variables was verified through network analysis. A structural equation model based on the results of network analysis and the factors influencing online loyalty and offline loyalty were analysed using the model. Therefore, independent variables except for perceived usability exhibited a positive effect on user satisfaction, and user satisfaction had a positive effect on loyalty. Furthermore, offline user satisfaction exhibited a positive effect on online loyalty, but online user satisfaction did not. Suggestions for future research and corporate strategy were provided. [ABSTRACT FROM AUTHOR]

Open innovation (OI) is a crucial strategy regardless of sector, public or private, or academic or practical. However, the concept itself is often considered abstract and broad. Therefore, this study explored the coauthorship network and its groups to empirically observe the phenomenon of an open innovation. It also examined the semantic network of subject fields in open innovation research. We used coauthorship data to observe collaboration among authors. To examine how an open innovation is conceptualised and explained in academia, we used the abstracts of papers and the classification data of the journals where the papers were published. The results of the analysis found a mainstream group, which is a small group-to-group connection. We observed that the small groups are connected by key authors. We found that a social network of authorship and a semantic network of abstracts are both closely related. Our results provide a deeper understanding of an open innovation. [ABSTRACT FROM AUTHOR]