No abstract

Many gamification designs in education do effectively mobilize students to some extent. Yet, there is still very little research to account for the specific influence on each student. It is essential to determine whether the students can be engaged by gamification in terms of various psychological factors. In this paper, the game element point was chosen to design the experiment. The experiments were used to engage students to ask more questions in class. The results indicated that gamified designs were effective in engaging people who were bashful or distracted. In addition, students were engaged more easily in social circumstances through a comparison of individual and social interactions. This research provides fertile ground for further gamification designs in education.

Many attempts at personalisation have been made in education. They all collect learning data and analyse learning behaviours, and ultimately achieve personalised learning dynamically. However, further research is needed on the ways to effectively access and analyse information about learning within an enjoyable environment and with positive results when realising personalised learning. In order to solve this problem, we connect the time in class and after class with semantic knowledge and combine these elements with gamification and a better interaction experience. We explore whether this teaching method can offer students a better learning experience and positive learning outcomes. Our approach plays an obvious role in personalised learning. Our results indicate that a teaching method which connects the two parts of a class with gamification and a means of interaction in AR (augmented reality) produces novel and enjoyable feelings, stimulates students' enthusiasm and improves the learning effects when they do personalised learning.

Improving health awareness is essential to health and healthcare sustainability. How to arouse attention to the health of people and encourage them to attend to healthcare progress so that we can reduce the costs of promoting healthcare by achieving more with less effort remains to be explored. In this paper, we provide a simplified health management app, called iTongue, with a basis in traditional Chinese medicine. People use iTongue to take pictures of their tongues to have a general idea of their health. We realize automated tongue image diagnosis using machine learning techniques to establish the relationship between the tongue image features and the cold or hot ZHENG (traditional Chinese medicine syndrome) in traditional Chinese medicine by learning through examples and assisting people to engage in health management. The results show that health management interaction based on traditional Chinese medicine has a positive influence on improving people's attention to their health, encouraging them to participate in health management activities and develop the habit of caring about their health over the long term. In the future, we could consider using this kind of traditional Chinese medicine idea as a means of publicity to engage people in healthcare and to assist healthcare sustainability development.