In recent years, MOOC has become one of the most popular trends in global education. However, the completion of courses is still a great challenge for MOOCs. Thus, the evaluation of MOOCs is of great importance to online education. The goal of this research is to evaluate the interfaces of localized MOOC on PC platforms, specifically, to explore the role of culture on the interface design and its user experience (UX). Three studies were conducted in our research. In study 1, through an interview, we selected two localized MOOCs (Chinese University MOOC and Coursera), typical user tasks, and main factors of UX. In study 2, a content analysis was conducted to compare the interface design of the MOOCs selected in study 1. The results showed significant cultural differences in the interface design between the two localized MOOCs. In study 3, the UX was evaluated on Chinese University MOOC (CUM) and Coursera. It is found that the task-based UX of CUM is better than Coursera on four typical tasks. And the overall UX (usability, aesthetics, and pleasure) is much higher on CUM. The findings reveal the cultural influence on the interface design of localized CUM and Course. Accordingly, the Chinese user experience is better on CUM than Course. This research indicates a better UX of localized MOOCs also depends on culture-preferred interface design. Meanwhile, from the perspective of UX, we also provide some theoretical and practical implications for the enhancement of interface designs of localized MOOCs. Hopefully, this research can contribute to the design of localized MOOCs in China.
The coronavirus disease 2019 (COVID-19) epidemic poses a threat to the everyday life of people worldwide and brings challenges to the global health system. During this outbreak, it is critical to find creative ways to extend the reach of informatics into every person in society. Although there are many websites and mobile applications for this purpose, they are insufficient in reaching vulnerable populations like older adults who are not familiar with using new technologies to access information. In this paper, we propose an AI-enabled chatbot assistant that delivers real-time, useful, context-aware, and personalized information about COVID-19 to users, especially older adults. To use the assistant, a user simply speaks to it through a mobile phone or a smart speaker. This natural and interactive interface does not require the user to have any technical background. The virtual assistant was evaluated in the lab environment through various types of use cases. Preliminary qualitative test results demonstrate a reasonable precision and recall rate.
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