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Task-Based Learning (TBL) is a student-centered, teacher-guided and task-performed teaching approach. This study was aimed to investigate the effects of task-based learning (TBL) in chemistry experiment teaching on promoting high school students’ critical thinking skills in Xi’an, China. To achieve the aims, a pre-test and post-test experimental design with an experimental group and a control group was employed. Students in the experimental group were taught with TBL, while students in the control group were taught with lecturing teaching methods. Five chemical experiments were selected, and 119 students aged at 17 - 19 voluntarily participated in the research which lasted one semester. The California Critical Thinking Skills Test (CCTST) was used as a data collection tool. Results showed there was an obvious significant difference (p < 0.05) in the dimension of analyticity in the experimental group after TBL, while there were no significant differences in the total score, the evaluation and inference of CCTST. The findings provide an effective way for chemistry teachers to improve students’ critical thinking analyticity skills.
In the present paper, we answer the question: for 0< a <1 fixed, what are the greatest value p(a)
and the least value q(a) such that the double inequality Jp(a,b)< aA(a,b)+ (1-a)G(a,b)<Jq(a,b)
holds for all a,b>0 with a is not equal to b ?
Brain-like computer research and development have been growing
rapidly in recent years. It is necessary to design large scale dynamical neural
networks (more than 106 neurons) to simulate complex process of our brain. But such kind of task is not easy to achieve only based on the analysis of partial differential equations,
especially for those complex neural models, e.g. Rose-Hindmarsh (RH) model. So
in this paper, we develop a novel approach by combining fuzzy logical designing
with Proximal Support Vector Machine Classifiers (PSVM) learning in
the designing of large scale neural networks. Particularly, our approach can
effectively simplify the designing process, which is crucial for both cognition
science and neural science. At last, we conduct our approach on an artificial
neural system with more than 108 neurons for haze-free task, and
the experimental results show that texture features extracted by fuzzy logic
can effectively increase the texture information entropy and improve the effect of
haze-removing in some degree.