Search

this research combines the artificial intelligence technique RNN/LSTM to develop a dialogue system, which mainly used in the bargaining unit of a negotiation course. The chatbot was applied in the dialogue of student drills in bargaining situations and investigates the feasibility of the dialogue system used in the course. The two-hour course has 48 second-year university students with different colleges and departments. The results show that most students have a positive view of instant messaging conducts dialogue exercises, and feel interesting. The groups targeting dialogue robots, students prefer courses. For groups with real people, students think it is more helpful for learning, and they have higher satisfaction with the results of bargaining negotiations.

Cognitive styles have been regarded as a crucial factor that affects the effectiveness of web-based learning (WBL). Previous research indicated that educational settings that match with students' cognitive styles can enhance students' learning performance, which is, however, linked to their emotion. Various physiological signals can be applied to measure emotion but the pulse is perhaps the most effective indicator. Thus, we conduct an exploratory research, which looks for a link between emotion and the matching/mismatching instructional approach with the condition of cognitive styles through a continuous pulse rate monitoring. The matching/mismatching instructional approach was delivered via a WBL system, which includes an index version and map version. The pulses of individual learners are collected by using a non-intrusive sensor. Our results indicate that the matching condition enables learners to feel more positive emotions than the mismatching condition, and is also linked to better learning perform...

Modern life has a strong tie with ICT technology, so as to the sensing technology which has played an important role than before. Its application is somewhat more than we have learned, such as education. Meanwhile, with the advance of software/hardware and the popularity of the Internet, e-books have drawn much of attention. With the introduction of the sensing technology to e-readers, it instills e-books the functions of reading or learning behavior. In self-learning situation, learners often suffer from detraction problem which cannot be easily detected and amended. In this study, we proposed a sensor-assisted learning system to monitor a learner's retention during the reading or learning process. The system has been incorporated into an e-book platform, or e-reader to become a personalized e-reader system. We proceed to conduct two experiments for sensor-assisted model (SAM) and e-book systems, respectively. The ultimate objective is to establish an adaptive personalized learning system by the feedback of data collected by sensors.

Modern lifestyle is closely associated with information technology, and sensor technology is particularly used, especially in learning and education. This study proposed a sensor-assisted learning system using sensor technology, in order to determine the learning retention of learners in the learning process, and further provide assistance or feedback. The identification rule of this system is constructed based on decision tree algorithm ID3 (C4.5). The system determined the learning retention according to the learners' visual attention recognition, sitting position variability, and physiological signals analysis.

In this study, we implemented a digital game-based learning (DGBL) system over Face book platform. For better understanding the impact of DGBL applied to social networking, the technology acceptance model (TAM) was employed for the evaluation. Results of this study showed that the DGBL incorporated into a social network website is a feasible and sound model for teaching. This study investigated the potential important design issues of the application over a social network website. It is believed that this study could bring teachers a better understanding how those characteristics of social networks can attribute to the success of users' learning.