Jing Wang

The goal of the present study is to explore whether the affective states of a pedagogical agent in an online multimedia lesson yields different learning processes and outcomes, and whether the effects of affective PAs depend on the learners’ emotion regulation strategies and their prior knowledge. In three experiments, undergraduates were asked to view a narrated animation about synaptic transmission that included either a happy PA or a neutral PA and subsequently took emotions, motivation, cognitive outcomes tests. Across three experiments, the happy PA group reported more positive emotions and higher level of motivation than the neutral PA group. Moreover, the happy PA prompted higher germane load than a neutral PA in Experiment 3. However, adding a happy PA to the screen did not improve learning performance. In addition, in Experiment 2, learners’ usage of emotion regulation strategies moderated the effectiveness of affective PA on positive emotions in learners. Specifically, happy PAs increased the positive emotions of students who used expressive suppression strategy but not those who used cognitive reappraisal strategy. In Experiment 3, the effectiveness of affective PAs was not moderated by learners’ prior knowledge. Results support the cognitive affective theory of learning with media that students are happier and more motivated when they learn from happy PAs than from neutral PAs.

This special theme brings together reflections and deliberations regarding the design, implementation, and development of data governance. By addressing “social data governance” as the keyword of the special theme, we aim to further the discussion on a contextual understanding of both the governing foundations and effects of data, dataism, and datafication in different societies. Such a discussion reminds us to pay particular attention to—and thus account for—the social dynamics that underpin and contextualize the design, operation, and promotion of quantified governing mechanisms in which information on social behaviors is collected, datafied, manipulated, and represented. Essentially, the social dynamics of data governance have existed for a long time and in many forms, ranging from credit bureaus’ scrutiny, evaluation, and labeling of their customers to internet-enabled massive data collection and scoring systems used by governments, and to automated contact tracing techniques as a centerpiece of dataveillance and infection control amid the COVID-19 pandemic. Nevertheless, scholarly work from a wide range of disciplines like law, mathematics, and business and with diverse geographical foci has not yet been comparatively and reflectively articulated. Being rich and diverse, the special theme advances such a requisite understanding of the status and relevance of social dynamics of data governance mechanisms based on a wide range of empirical cases around the globe. To scrutinize the social dynamics helps illuminate and contrast divergent manifestations of data governance and their underlying mechanisms.

The financial applications of data technology have enabled the rise of Chinese fintech industries. As part of people's everyday lives, fintech apps have helped companies collect vast amounts of user data for business profit and social good. This paper takes an open-systems approach to study the constructs of this emerging idea of data governance, particularly its operational logic, involved stakeholders, and socio-cultural consequences in the context of fintech industries in China. It asserts that data governance at the company level has been realized through three types of tasks: standardization, configuration, and monetization of big data. These tasks are oriented by the imperative of business innovation which is considered pivotal for the company to survive the competition. An ensemble of internal and external actors joined the governing process, but internal actors hold the stake. The goal of innovation drives the companies to speedily collect data from a wider variety of sources, thus having to establish more sophisticated systems to manage and utilize those data. These complicated systems, however, have urged the government to strengthen regulatory controls alongside the general support of business innovation. This study unveils the performative aspects of big-data-based innovation at fintech firms. It also helps to understand the pathology of the innovation-governance paradox shared in the data economy in the global context.

Dynamic modulation of cell adhesion is integral to a wide range of biological processes. The small guanosine triphosphatase Rap1 is an important regulator of cell - cell and cell - matrix adhesions. We show here that induced expression of activated Abl tyrosine kinase reduces Rap1-GTP levels through phosphorylation of Tyr221 of CrkII, which disrupts interaction of CrkII with C3G, a guanine nucleotide exchange factor for Rap1. Abl-dependent down-regulation of Rap1-GTP causes cell rounding and detachment only when the Rho - ROCK1 pathway is also activated, for example, by lysophosphatidic acid. During ephrin-A1 - induced retraction of PC3 prostate cancer cells, we show that endogenous Abl is activated and disrupts the CrkII - C3G complex to reduce Rap1-GTP. Interestingly, ephrin-A1 - induced PC3 cell retraction also requires LPA, which stimulates Rho to a much higher level than that is activated by ephrin-A1. Our results establish Rap1 as another downstream target of the Abl - CrkII signaling module and show that Abl - CrkII collaborates with Rho - ROCK1 to stimulate cell retraction. © 2008 Huang et al.