No abstract

No abstract

Abstract. Previous personalized DTV recommendation systems focus only on viewers' historical viewing records or demographic data. This study proposes a new recommending mechanism from a user oriented perspective. The recommending mechanism is based on user properties such as Activities, Interests, Moods, Experiences, and Demographic information-AIMED. The AIMED data is fed into a neural network model to predict TV viewers' program preferences. Evaluation results indicate that the AIMED model significantly increases recommendation accuracy and decreases prediction errors compared to the conventional model.

No abstract

"Building information technology" and "cost estimating" are two core skills of construction education. However, in traditional education, students learn these two important subjects in separate courses. This study proposes a blended learning environment which can provide students with support for their face-to-face learning activities in the classroom and also give them the opportunity of "learning by doing" through their practice with online construction projects in the web-based BIM (building information modeling) & cost estimating system. Then the TAM3 (Technology Acceptance Model 3) theory was used to compare the expert and novice students' acceptance of this blended learning model. Finally, the path analysis method was used to verify the research hypotheses developed in this study based on the TAM3 method and then further explore the cause-effect among the TAM3 variables in these hypotheses. Our result found that the blended learning environment developed in this study was generally accepted by all the participating students and it could also enhance the students' acceptance of the blending learning strategy that combines classroom-based education and on-line learning. Even though there are significant differences between novices and experts in certain variables as found in this study, students can still achieve desirable learning results through repeated and continuous practice and learn how to solve problems through "learning by doing" and discussions with their peers inside and outside the classroom. As a consequence, they will have better learning results in the end.