Research on Compatible Mode of Self-directed Learning and Cooperative Learning in Blended Teaching of Basic English Course

In the information age,blended teaching,no matter online or offline,has become the mainstream of college teaching reform.In this teaching model,self-directed learning and cooperative learning are the two main learning approaches.On the online teaching platform,students mainly learn knowledge-based content by self-directed learning,while practising their language skills by cooperative learning in flipped classroom activities.On one hand,it advocates student-centered strategy so as to improve students autonomous learning ability;on the other hand,teachers serve as a guide to organize the classroom activities;meanwhile,they give timely feedback to students in order to promote students’learning ability.In blended teaching model,this mutually compatible and reinforcing model of self-directed learning and cooperative learning is undoubtedly helpful to improve the teaching efficiency.

Innovative Research on the Blending Learning Mode of Econometrics

Due to the outbreak of the Covid-19 in 2020,online education has become the mainstream.After the epidemic,the blending learning mode has also become a key goal of the teaching reform of colleges and universities,and the blending learning mode of various courses has blossomed everywhere.In this context,this paper used the Econometrics course as the carrier,analyzed the many unreasonable problems in the traditional Econometrics course,and proposed an optimization plan and path for the blending learning mode to address these problems.

Construction of Chinese Learning Mode for Overseas Students in Higher Vocational Colleges under the Background of the Belt and Road Initiative

With the deepening of exchanges between China and other countries,especially the proposal of the Belt and Road Initiative,more and more foreign students come to China to study,putting forward higher requirements for the education and management of colleges and universities in China.In the process of implementing the strategy of"one belt and one road",language interaction is the basic prerequisite for achieving exchanges and cooperation among different countries.In the face of this situation,by analyzing the existing problems in the training of overseas students in higher vocational colleges in China under the background of"One Belt and One Road"strategy,in this paper,the construction of the Chinese learning mode for overseas students in higher vocational colleges was put forward,hoping to provide help for the training of overseas students and solve the problem of foreign students'language learning.

上海市级定点医院新型冠状病毒肺炎患者集中救治动态能力体系建设策略

2022年上海本轮疫情中,上海申康医院发展中心组成工作专班,通过发挥知识转移与组织动态能力组织传导策略,协同各类资源,搭建多元动态平台,提高市级医院应对内外部环境压力的能力,增强市级医院在疫情期间的救治体系以及救治能力。现总结在公共卫生应急状态下如何组织市级医院通过整合内在与外在资源转型成为集中救治定点医院,建立市级医院“一夜成军”的快速反应机制。

Cultivation of Innovation Ability of Students in the Discipline of Food Science and Engineering from the Perspective of Engineering Professional Certification

Cultivating the top-notch innovative talents is an essential task for connotative construction of higher education.As an applicationoriented discipline,the Discipline of Food Science and Engineering attaches great importance to the cultivation of innovation ability of college students.For a long time,however,the discipline education has problems of the inverted teaching subject position,weak coordination ability and single practice mode.The support for the cultivation of innovation ability is weak and ineffective.Therefore,in the context of professional certification of engineering education,it is necessary to make reform of traditional education mode and improve the carrier support and target acquisition taking the Outcomes-based Education(OBE)as guide,the innovation ability cultivation as objective,to provide effective guarantee for cultivation of the top-notch talents.These have become issues that should not be ignored in the development of the Discipline of Food Science and Engineering.

Multi-label active learning by model guided distribution matching

Multi-label learning is an effective framework for learning with objects that have multiple semantic labels, and has been successfully applied into many real-world tasks, In contrast with traditional single-label learning, the cost of la- beling a multi-label example is rather high, thus it becomes an important task to train an effective multi-label learning model with as few labeled examples as possible. Active learning, which actively selects the most valuable data to query their labels, is the most important approach to reduce labeling cost. In this paper, we propose a novel approach MADM for batch mode multi-label active learning. On one hand, MADM exploits representativeness and diversity in both the feature and label space by matching the distribution between labeled and unlabeled data. On the other hand, it tends to query predicted positive instances, which are expected to be more informative than negative ones. Experiments on benchmark datasets demonstrate that the proposed approach can reduce the labeling cost significantly.

An ensemble learning model for driver drowsiness detection and accident prevention using the behavioral features analysis

Purpose-In order to prevent accidents during driving,driver drowsiness detection systems have become a hot topic for researchers.There are various types of features that can be used to detect drowsiness.Detection can be done by utilizing behavioral data,physiological measurements and vehicle-based data.The existing deep convolutional neural network(CNN)models-based ensemble approach analyzed the behavioral data comprises eye or face or head movement captured by using a camera images or videos.However,the developed model suffered from the limitation of high computational cost because of the application of approximately 140million parameters.Design/methodology/approach-The proposed model uses significant feature parameters from the feature extraction process such as ReliefF,Infinite,Correlation,Term Variance are used for feature selection.The features that are selected are undergone for classification using ensemble classifier.Findings-The output of these models is classified into non-drowsiness or drowsiness categories.Research limitations/implications-In this research work higher end camera are required to collect videos as it is cost-effective.Therefore,researches are encouraged to use the existing datasets.Practical implications-This paper overcomes the earlier approach.The developed model used complex deep learning models on small dataset which would also extract additional features,thereby provided a more satisfying result.Originality/value-Drowsiness can be detected at the earliest using ensemble model which restricts the number of accidents.

Reimagining Modern Education: Contributions from Modern Japanese Philosophy and Practice?

Purpose:Amidst ongoing attempts to think beyondWestern frameworks for education,there is a tendency to overlook Japan,perhaps because it appears highly modern.This is striking given that some prominent strands of Japanese philosophy have formulated an explicit and exacting challenge to the core onto-epistemic premises of modern Western thought.It is also surprising because Japanese educational practices have resulted in some of the highest achievement outcomes—both cognitive and noncognitive—found anywhere in the world and inculcate a worldview that is distinct.Design/Approach/Methods:Herein,we thus attempt to make visible the potential contribution of modern Japanese philosophy by outlining some of the core ideas,then turn to sketch resonances with and responses to other projects outlined in this Special Issue.Our approach is elucidation through relational comparison.Findings:Through this process,we suggest that the notion of self-negation as a mode of learning may be helpful in explaining why—at the empirical level—the outlook of Japanese students,and perhaps other East Asian students,diverge markedly from their Western peers.Yet we also find that an attempt,such as ours,to link divergent onto-epistemic thought to alternative empirical hypotheses quickly gives rise to various doubts and discomforts,even among otherwise sympathetic scholars.Originality/Value:In directly responding to these doubts,one original contribution of our piece is to show just how difficult it may ultimately be to divest from the symbolic foundations already laid by Western liberalism:Even if divergent thought can be imagined and different cultural narratives explored,dominant readings of empirical“realities”continue to be entrapped in the logic laid by Western liberalism.