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New media technology can effectively support teacher–student rapport. In this study, Chinese students befriended their teachers on social media, and we compared their blended learning (N=455) based on this social media interaction with face-to-face learning (N=450). The results indicate that affective learning and cognitive learning in blended learning were superior to face-to-face learning. However, no significant differences in social presence, academic self-concept, or grade point average were observed between blended learning and face-to-face learning. According to a multi-group structural equation modelling analysis, the mediating effect of affective learning in blended learning was superior to that in face-to-face learning; in addition, academic self-concept significantly influenced cognitive learning. No significant difference was found for grade point average. Finally, we propose blended learning related suggestions regarding how to trigger students' connection need and inspire their wisdom and potential. [ABSTRACT FROM AUTHOR]

Application of artificial intelligence is accelerating the digital transformation of enterprises, and digital content optimization is crucial to take the users' attention in social media usage. The purpose of this work is to demonstrate how social media content reaches and impresses more users. Using a sample of 345 articles released by Chinese small and medium-sized enterprises (SMEs) on their official WeChat accounts, we employ the self-determination theory to analyze the effects of content optimization strategies on social media visibility. It is found that articles with enterprise-related information optimized for content related to users' psychological needs (heart-based content optimization, mind-based content optimization, and knowledge-based content optimization) achieved higher visibility than that of sheer enterprise-related information, whereas the enterprise-related information embedded with material incentive (benefits-based content optimization) brings lower visibility. The results confirm the positive effect of psychological needs on the diffusion of enterprise-related information, and provide guidance for SMEs to apply artificial intelligence technology to social media practice. [ABSTRACT FROM AUTHOR]

Few studies have examined the relationship between personality traits and social networking sites (SNSs) with a dominant concentration on the personality alterations under SNSs influence. The relationship between personality and privacy control was less focused and discussed. In order to figure out the internal mechanism of such link among youth SNSs users, the Theory of Planned Behavior (TPB) was extended by including Five-Factor Model of Personality to explore how personality traits interact with privacy control behavior on SNSs. The investigation using the theoretical method mentioned led to several hypotheses which were later assessed by an online study conducted within randomly chosen college students (N = 201) from two randomly chosen universities in China. This sampling strategy was designed to mimic the situation of targeted research population in the most reasonable way. The results suggested neuroticism and openness predicted SNSs privacy. Neuroticism and openness predicted "networked privacy" was also found. Theoretical implications of these findings were addressed. [ABSTRACT FROM AUTHOR]

In online learning, the high dropout ratio is a serious problem and reflects a poor level of motivation in e-learning programmes. Social-interactive engagement may greatly affect users' attitudes and choices in many fields; among these, online learning is inevitably impacted by factors such as social connections. To study the impact of social-interactive engagement on the dropout ratio and learning progress, iMOOC was employed as the study object using data from 619 courses and 2,071,147 learners, as well as 19,451,428 learning records. As engagement is a process of collecting experiences, the learner's experience plays a significant role in reducing the dropout ratio. Social-interactive engagement helps to reduce the dropout ratio; thus, learners should be encouraged to engage in online activities, such as discussions, note sharing, commenting and Q&A, to alleviate the feelings of being disconnected and isolated. Through an empirical study, we also find that the longer a learner's registered time is, the lower the dropout ratio. From the perspective of the courses themselves, the dropout ratios of shorter or more difficult courses are lower than those of longer or less-difficult courses. This paper provides theoretical and practical recommendations for reducing the dropout ratio in online learning and improving learning efficiency. [ABSTRACT FROM AUTHOR]

With the growth of social media communities, people now use this new media to engage in many interrelated activities. As a result, social media communities have grown into popular and interactive platforms among users, consumers and enterprises. In the social media era of high competition, increasing continuance intention towards a specific social media platform could transfer extra benefits to such virtual groups. Based on the expectation-confirmation model (ECM), this research proposed a conceptual framework incorporating social influence and social identity as key determinants of social media continuous usage intention. The research findings of this study highlight that: (1) the social influence view of the group norms and image significantly affects social identity; (2) social identity significantly affects perceived usefulness and confirmation; (3) confirmation has a significant impact on perceived usefulness and satisfaction; (4) perceived usefulness and satisfaction have positive effects on usage continuance intention. The results of this study can serve as a guide to better understand the reasons for and implications of social media usage and adoption. [ABSTRACT FROM AUTHOR]