The higher education sector has seen a shift in teaching approaches over the past decade with an increase in the use of video for delivering lecture content as part of a flipped classroom or blended learning model. Advances in video technologies have provided opportunities for students to now annotate videos as a strategy to support their achievement of the intended learning outcomes. However, there are few studies exploring the relationship between video annotations, student approaches to learning, and academic performance. This study seeks to narrow this gap by investigating the impact of students' use of video annotation software coupled with their approaches to learning and academic performance in the context of a flipped learning environment. Preliminary findings reveal a significant positive relationship between annotating videos and exam results. However, negative effects of surface approaches to learning, cognitive strategy use and test anxiety on midterm grades were also noted. This indicates a need to better promote and scaffold higher order cognitive strategies and deeper learning with the use of video annotation software.

Background To mitigate air pollution-related health risks and target interventions towards the populations bearing the greatest risks, the City Health Outlook (CHO) project aims to establish multi-scale, long-lasting, real-time urban environment and health monitoring networks. A major goal of CHO is to collect data of personal exposure to particulate air pollution through a full profile that consists of a matrix of activities and micro-environments. As the first paper of a series, this paper is targeted at illustrating the characteristics of the participants and examining the effects of different covariates on personal exposure at various air pollution exposure levels. Methods In the first campaign, volunteers are recruited to wear portable environmental sensors to record their real-time personal air pollution exposure and routes. After a web-based social media recruitment strategy, 50 eligible subjects joined the first campaign in Beijing from January 8 to January 20, 2018. The mean personal exposures were measured at 19.36, 37.65, and 43.45 μg/m 3 for particulate matter (PM) with a diameter less than 1, 2.5, and 10 μm, respectively, albeit with the high spatial-temporal variations. Results Unequal distribution of exposures was observed in the subjects with different sociodemographic status, travel behavior, living and health conditions. Quantile regression analysis reveals that subjects who are younger, less educated, exposed to passive smoking, low to middle household income, overweight, without ventilation system at home or office, and do not possess private vehicles, are more susceptible to PM pollution. The differences, however, are generally insignificant at low exposure levels and become evident on bad air quality days. Conclusions The heterogeneity in personal exposure found in this the first CHO campaign highlighted the importance of studying the pollution exposure at the individual scale. It is at the critical stage to bridge the knowledge gap of environmental inequality in different populations, which can lead to great health implications. Electronic supplementary material The online version of this article (10.1186/s12889-019-7022-8) contains supplementary material, which is available to authorized users.

Various health care devices owned by either hospitals or individuals are producing huge amount of health care data. The big health data may contain valuable knowledge and new business opportunities. Obviously, cloud is a good candidate to collect, store and analyse such big health care data. However, health care data is very sensitive for its owners, and thus should be well protected on cloud. This paper presents our solution to protecting and analyzing health care data stored on cloud. First, we develop novel technologies to protect data privacy and enable secure data sharing on cloud. Secondly, we show the methods and tools to conduct big health care data analysis. Finally, both the security technology and the data analysis methods are evaluated to show the usefulness and efficiency of our solution.

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As a new technology, cloud computing brings a change to business models and ways of working and provides convenience to the way that people work, study and life. User data of cloud computing are stored in the "cloud". The loss of data and the disclosure of privacy will give users a significant loss, so that people are increasingly concerned about its security. The industry of cloud computing has a huge market growth prospects, but compared to other security products, cloud computing access risks exist in the data integrity, data recovery, and privacy, and risks of safety assessment in electronic services, business compatibility and third-party audit regulations.