KEYWORDS: Emotion, Image processing, Education and training, Data modeling, Design and modelling, Research management, Analytical research, Human-machine interfaces
With the diversification and popularization of intelligent technology, how to integrate education into contemporary technology to get improvement in teaching always is the research direction people are crazy in. The traditional teaching mode is updating and evolving round after round. The significance and effect of them not only stay in technological innovation, but also reflect and achievements. Otherwise, all the evolution just stay on the surface without meaning. This research will focus on the connection between the emotion-detection and learning efficiency. The specific meaning of implementation includes two points. The first point is about assisting the class management through emotion-detection technology. According to a number of research reports, there is a huge correlation between emotion and learning efficiency. In addition, teaching forms have become more and more diversified. From online to offline, diversification usually be accompanied with problems that is how to inspect Learning effectiveness because of the traditional test and task point just have little limited effect. The second point is actually the detection of the content of courses. Through emotion recognition, it can accurately reflect whether knowledge points in the classroom is reasonable or not. The feedback from students can be detected through real-time data. The system is based on the keras deep learning framework and open CV source library to achieve emotion detection. Finally data visualization displays learning efficiency.
With the development of information technology, the teaching of IoT technology has gradually become popular, but as an important part of hands-on training, the practical aspects of the course are restricted by various factors such as equipment and venue, resulting in unsatisfactory results. Through the introduction of virtual simulation technology in teaching, the IoT programming course is no longer constrained by the above factors, so that the course can reflect the characteristics of IoT applications, improve the implementation effect and teaching quality of the IoT programming course, and stimulate students' interest in learning.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.