In this paper, the study aims to inquire into the impact of integrating creative thinking teaching through project-based learning in the engineering course. In the beginning, the quasi-experiment is implemented in the engineering course. The lecture-based teaching strategy is applied to the control group, while the experimental group applied the project-based learning strategy. All of the students are asked to propose their draft scheme of final project in the middle term, and then implement one system prototype as the final project in the end of semester. The draft scheme and prototype are reviewed by experts for measuring whether creativity has increased or not. Finally, a satisfaction questionnaire is delivered to evaluate the students’ opinions about the experimental classroom. The results show that the project-based learning approach is able to promote the creative thinking of students, especially with regard to fluency and flexibility. Moreover, the students in their interview thought suitable creativity thinking tools are an approach that can promote their creativity significantly. Hence, the various creative thinking tools must be provided for students in order to take advantage of developing creativity thinking habits.

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In this study, the head-mounted virtual reality (VR) technology is adpoted for computational thinking teaching in the AIoT Maker course teaching. The earthquake relief situation is designed in the VR in the course scenario, because in the context of situational thinking, pre-emptive training in the face of emergency disasters has been conducted through observation meetings or training courses. Through listening to lecturers or experienced personnel to share experiences, students often have a harder time thinking about real scenes and it is harder to think creatively how to design with the emergency disaster response. In view of this, this research will combine the development and evaluation of earthquake relief training courses for head-mounted VR and computational thinking experiments to explore the use of VR and computational thinking experiments to drive students to create ideas for real disaster relief scenarios. Through computational thinking, students think about different script situations and discuss in each scene to find a suitable maker design of the AIoT project. Finally, this study combined with its modular space program training to develop students' programming skills. According to the experiment, this study is able to strength students' practical learning motivation, and follow-up employ ability training for course learning.

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As cloud computing and wearable devices technologies mature, relevant services have grown more and more popular in recent years. The healthcare field is one of the popular services for this technology that adopts wearable devices to sense signals of negative physiological events, and to notify users. The development and implementation of long-term healthcare monitoring that can prevent or quickly respond to the occurrence of disease and accidents present an interesting challenge for computing power and energy limits. This study proposed an adaptive sensor data segments selection method for wearable health care services, and considered the sensing frequency of the various signals from human body, as well as the data transmission among the devices. The healthcare service regulates the sensing frequency of devices by considering the overall cloud computing environment and the sensing variations of wearable health care services. The experimental results show that the proposed service can effectively transmit the sensing data and prolong the overall lifetime of health care services.

In recent years, the learning efficacy of online to offline (O2O) teaching methods seems to outperform traditional teaching methods in the field of education. Students can use a small private online course (SPOC) teaching platform to preview class-related materials, learn basic knowledge, and enhance the practical experience of system development in offline courses. The research team applied an artificial intelligence (AI) precision education strategy to design a teaching experiment that evaluated whether this approach may lead to better learning outcomes. In addition to questionnaire surveys to ascertain students' attitudes toward and their satisfaction with learning, this study employed in-depth interviews to understand a potential influence on changes in teachers' curriculum design and teaching approaches when SPOCs was integrated into the traditional university classroom, as well as the impact of the AI precision education model. The results showed that the AI precision education model may facilitate students' learning experience and enhance student achievement.