Against the background of "architecturalization" of public art, the significance of architectural color design lies not only in the visual element of architectural environment, but also in the emotion expres...Against the background of "architecturalization" of public art, the significance of architectural color design lies not only in the visual element of architectural environment, but also in the emotion expression of city culture and spirit of the time. Architectural colors should be constructed from the 6 aspects, namely, conveying city spirit, coordinating the environment, showing regional characteristics, reflecting public concept, obtaining public sympathy, combining cultural connotations of color and functions of space. Moreover, the impact of regional culture on architectural color should be properly handled, the emotions of architecture for the city reflected on the surface of architecture, which can reverse the convergence of city images to some extent, and promote the diversity of regional humanistic architectural landscapes.展开更多
Prior studies have shown the importance of classroom dialogue in academic performance,through which knowledge construction and social interaction among students take place.However,most of them were based on small scal...Prior studies have shown the importance of classroom dialogue in academic performance,through which knowledge construction and social interaction among students take place.However,most of them were based on small scale or qualitative data,and few has explored the availability and potential of big data collected from online classrooms.To address this issue,this paper analyzes dialogues in live classrooms of a large online learning platform in China based on natural language processing techniques.The features of interactive types and emotional expression are extracted from classroom dialogues.We then develop neural network models based on these features to predict high-and low-academic performing students,and employ interpretable AI(artificial intelligence)techniques to determine the most important predictors in the prediction models.In both STEM(science,technology,engineering,mathematics)and non-STEM courses,it is found that high-performing students consistently exhibit more positive emotion,cognition and off-topic dialogues in all stages of the lesson than low-performing students.However,while the metacognitive dialogue illustrates its importance in non-STEM courses,this effect cannot be found in STEM courses.While high-performing students in non-STEM courses show negative emotion in the last stage of lessons,STEM students show positive emotion.展开更多
文摘Against the background of "architecturalization" of public art, the significance of architectural color design lies not only in the visual element of architectural environment, but also in the emotion expression of city culture and spirit of the time. Architectural colors should be constructed from the 6 aspects, namely, conveying city spirit, coordinating the environment, showing regional characteristics, reflecting public concept, obtaining public sympathy, combining cultural connotations of color and functions of space. Moreover, the impact of regional culture on architectural color should be properly handled, the emotions of architecture for the city reflected on the surface of architecture, which can reverse the convergence of city images to some extent, and promote the diversity of regional humanistic architectural landscapes.
基金This work was supported by the Center for Social Network Research of Tsinghua University,Tsinghua’s Research Project(No.2016THZWYY03)the Project of Tencent Social Research Center(No.20162001703).
文摘Prior studies have shown the importance of classroom dialogue in academic performance,through which knowledge construction and social interaction among students take place.However,most of them were based on small scale or qualitative data,and few has explored the availability and potential of big data collected from online classrooms.To address this issue,this paper analyzes dialogues in live classrooms of a large online learning platform in China based on natural language processing techniques.The features of interactive types and emotional expression are extracted from classroom dialogues.We then develop neural network models based on these features to predict high-and low-academic performing students,and employ interpretable AI(artificial intelligence)techniques to determine the most important predictors in the prediction models.In both STEM(science,technology,engineering,mathematics)and non-STEM courses,it is found that high-performing students consistently exhibit more positive emotion,cognition and off-topic dialogues in all stages of the lesson than low-performing students.However,while the metacognitive dialogue illustrates its importance in non-STEM courses,this effect cannot be found in STEM courses.While high-performing students in non-STEM courses show negative emotion in the last stage of lessons,STEM students show positive emotion.
