Small-class teaching has seemed to become one of the trends of education reforms worldwide as professional associations and school boards struggle to provide quality education. Many countries have implemented small-cl...Small-class teaching has seemed to become one of the trends of education reforms worldwide as professional associations and school boards struggle to provide quality education. Many countries have implemented small-class teaching for many years. And therefore it has become a challenging activity for teachers to teach in small classes. This paper mainly focuses on the characteristics of small-class teaching, planning and skills needed for group management, small class discussion techniques and strategies of what to do when things go wrong in group sessions.展开更多
Recently,small class course teaching,with less than 30 students,seems to outperform the traditional large class course teaching in the field of education.Students can use online private course platform to preview cour...Recently,small class course teaching,with less than 30 students,seems to outperform the traditional large class course teaching in the field of education.Students can use online private course platform to preview course-related knowledge and promote practical experiences of offline courses.In this study,an evaluation strategy has been proposed for precision education protocol in small class course(SCC)based on artificial intelligence(AI),with the goal of focusing on the curriculum design and teaching approaches.By using the AI precision education model,the teaching approaches of SCC can be integrated into the traditional classroom.The results showed that the AI precision education model can promote the learning outcomes and enhance students’learning achievements.展开更多
Traditional classification algorithms perform not very well on imbalanced data sets and small sample size. To deal with the problem, a novel method is proposed to change the class distribution through adding virtual s...Traditional classification algorithms perform not very well on imbalanced data sets and small sample size. To deal with the problem, a novel method is proposed to change the class distribution through adding virtual samples, which are generated by the windowed regression over-sampling (WRO) method. The proposed method WRO not only reflects the additive effects but also reflects the multiplicative effect between samples. A comparative study between the proposed method and other over-sampling methods such as synthetic minority over-sampling technique (SMOTE) and borderline over-sampling (BOS) on UCI datasets and Fourier transform infrared spectroscopy (FTIR) data set is provided. Experimental results show that the WRO method can achieve better performance than other methods.展开更多
文摘Small-class teaching has seemed to become one of the trends of education reforms worldwide as professional associations and school boards struggle to provide quality education. Many countries have implemented small-class teaching for many years. And therefore it has become a challenging activity for teachers to teach in small classes. This paper mainly focuses on the characteristics of small-class teaching, planning and skills needed for group management, small class discussion techniques and strategies of what to do when things go wrong in group sessions.
基金The High Level Innovation Team Construction Project of Beijing Municipal Universities(Project Number:IDHT20190506).
文摘Recently,small class course teaching,with less than 30 students,seems to outperform the traditional large class course teaching in the field of education.Students can use online private course platform to preview course-related knowledge and promote practical experiences of offline courses.In this study,an evaluation strategy has been proposed for precision education protocol in small class course(SCC)based on artificial intelligence(AI),with the goal of focusing on the curriculum design and teaching approaches.By using the AI precision education model,the teaching approaches of SCC can be integrated into the traditional classroom.The results showed that the AI precision education model can promote the learning outcomes and enhance students’learning achievements.
文摘Traditional classification algorithms perform not very well on imbalanced data sets and small sample size. To deal with the problem, a novel method is proposed to change the class distribution through adding virtual samples, which are generated by the windowed regression over-sampling (WRO) method. The proposed method WRO not only reflects the additive effects but also reflects the multiplicative effect between samples. A comparative study between the proposed method and other over-sampling methods such as synthetic minority over-sampling technique (SMOTE) and borderline over-sampling (BOS) on UCI datasets and Fourier transform infrared spectroscopy (FTIR) data set is provided. Experimental results show that the WRO method can achieve better performance than other methods.
