Whether families using big data-based digital payments will increase household healthcare expenditure is a subject that needs to be investigated in the era of big data. Based on the data from China Family Panel Studies (CFPS), 24,126 samples from 2014 to 2018 are used to examine the impact and mechanism of big data-based digital payments on household healthcare expenditure. The empirical results of this paper show that the use of digital payments by households can significantly increase household healthcare expenditure with the empowerment of big data. This research employs the instrumental variable method to verify and produce consistent estimation results in order to address potential endogeneity issues such as measurement error and missing variables. We learn via mechanism analysis that household adoption of big data-driven digital payments can remove credit limitations and build social capital, resulting in higher household health-care spending. We also perform a heterogeneity analysis. The findings reveal that when a family's traditional financial accessibility is high, the head of the household is young or middle-aged, and the head of the household has a higher level of education, digital payment will play a larger role in encouraging household healthcare expenditure. The conclusions of this paper are still solid after changing the indicators of household healthcare expenditure substituting the indicators of digital payment, and adjusting the variables. As a result, this article provides micro-evidence for the usage of digital payments by households to enhance healthcare spending.JEL ClassificationD12 G21 O30 O53 I12

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Doctoral students need guidance from both language teachers and academic supervisors for academic publication. However, previous studies have predominantly focused on corrective feedback from language teachers. The small number of studies on supervisory feedback were mainly undertaken in English-speaking countries on theses and dissertations, and mostly examined supervisors in applied linguistics, who probably have much in common with language professionals. To fill the research gaps, we investigated the foci of the feedback from a non-English-speaking supervisor on drafts of his doctoral students’ research article intended for a top conference in computer science. The results show that the supervisor commented not only on the content but also on the requirements for research writing, the logical flow of ideas, surface-level language issues, and visual elements. The findings can inform language teachers of what supervisors may value so that language professionals can provide feedback that better caters to the needs of students in research writing.

Abstract-This study analyzed the interactive behaviours among students in online course forum. The subject of this study was 30 students who participated in a course. The course was delivered in a mixed mode which contained online mode and face-to-face mode. The whole semester was divided into three six-week periods which represented the earlier stage, the mid stage and the late stage of the semester. The online relation networks were respectively reconstructed among the participants according to the interactive behaviours in the forum by Social Network Analysis method. The relation networks among the students in the course forum were high-density networks. The students in these networks got in touch with most active participants and information could be shared among most participants. The important indicators such as "density", "mean distance" and "reciprocity" in the three periods of the semester were calculated. The results showed that the characteristics of the relation networks generated in the three periods differed. Finally, some suggestions were propsed for teacher, limitations and further research plans were proposed.