Providing the minds of the out-of-the-box digitalization as the basic component of the information culture of the teacher

Pistunova, Tetiana; Slabko, V. M.; Averina, Kateryna; Romanchenko, Inna; Babakina, Oksana; Відоменко, Оксана Іванівна

doi:10.24115/s2446-62202021721076p.691-696

Cited by 3 publications

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“…The huge amount of learning resources can easily cause us to be lost in resources, and we cannot find the most suitable learning resources among many learning resources quickly [ 3 ]. Deep learning technology, speech recognition technology, face recognition technology, and other intelligent technologies have been widely used in other fields, bringing numerous conveniences to our production life and getting good evaluations [ 4 ]. Therefore, how to use intelligent technology to realize personalized recommendations of learning resources has become a hot and difficult research point in the field of education.…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of English Online Learning Based on Deep Learning

Jie

Liu

et al. 2022

Computational Intelligence and Neuroscience

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With the popularization of the Internet lifestyle and the innovation of learning methods, more and more online learning systems have emerged, allowing users to study in the system anytime and anywhere. While providing convenience to users, online learning systems also bring troubles to users, who cannot quickly find the resources they are interested in from the huge amount of learning resources. In this paper, we apply deep learning to an English online learning platform and analyze learners and learning contents by clustering algorithm and association rules. Based on this, a content organization system is developed using genetic algorithms, which is applied to the case of this paper to provide learners with personalized learning content. With the hope that the system can be extended to other online learning platforms in the future, three data mining techniques were selected to solve the problems found in the English online learning platform, and we designed how these techniques should be applied to the online learning platform. The first technique is the cluster mining technique, which is used to analyze learners’ profiles, classify learners in different categories, provide them with personalized learning content, and organize group learning. The second technique is association rules, which is used to analyze the correlation between learning contents. For the adaptive student-teacher knowledge migration strategy, the teacher model can guide the student model to track online and migrate the task-specific knowledge to the online tracking student model through the network parameters. Finally, a case study is selected and the above design is applied to this case study, and the results are analyzed in detail. The data mining technology is applied to the English online learning platform, and an innovative English learning content organization system is developed. It is hoped that the results of this study will have some practical value for promotion and provide an idea for the construction of the online learning platform, and it is also expected that the idea can improve the quality of online learning to a certain extent. Specifically, the online student model is adaptively updated by the teacher model parameters and the online student model parameters together.

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Section: Introductionmentioning

confidence: 99%

Effectiveness of English Online Learning Based on Deep Learning

Jie

Liu

et al. 2022

Computational Intelligence and Neuroscience

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“…With the massive amount of information data, practitioners are required to explore new processing modes in the big data system in order to obtain e ective information from it, use it, and analyze it with data mining and machine learning methods and other technical [10]. It can be seen that collecting massive and diversi ed kinds of information data and using technical means to obtain and predict the statistical laws of things will assist in improving the ability of making various decisions by the state, enterprises, and individuals [11].…”

Section: Introductionmentioning

confidence: 99%

Construction of Enterprise English Adaptive Learning Platform Based on Big Data Analysis

Luo

2022

Scientific Programming

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With the rise of “Internet+” as a national strategy, traditional industries have accelerated their integration with the Internet, and the education industry has also begun to seek innovative development. The fast-paced life of modern people makes time for learning more fragmented, and the high pressure of life makes people want to avoid excessive pressure from learning. These give opportunities and advantages to the development of online education, which is more adaptable to fragmentation and light weight. Online learning effectively solves the drawbacks of imbalance between supply and demand of offline education by solving the problems of time, distance, capacity, and scarcity of educational resources. In this paper, we take H International Education Group as the research subject. The paper combines the practice of precise English teaching theory and big data technology analysis tools to study the optimization of English teaching strategies in the K12 English training product market of H International Education Group. The materials prevalent in the English vocabulary market today are “one-size-fits-all,” presenting the same vocabulary resources to all learners without taking into account the differences in learning styles, learning preferences, and original cognitive structures of different learners.

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Digitalization and Information Management Mechanism of Sports Events Based on Multisensor Node Cooperative Perception Model

et al. 2022

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In the process of developing major sports events, how to guide providers and users to provide and utilize the archives information resources of major sports events and realize the interaction between them is an important problem to be solved urgently in the development of major sports events and the archive service of major sports events. By analyzing the present situation of archive service of major sports events, especially the analysis of the opposite dependent subjects of service providers and users, we can see that the continuous development of archive services for major sports events will inevitably lead to constant changes in user groups and user needs, guided by the theory of information retrieval, knowledge management, and media effect. According to the service model of archive service of major sports events, the archive service model of specific sports events is constructed. In this paper, four kinds of event recommendation models are applied to the collected marathon event data for experiments. Through experimental comparison, the effectiveness of content-based recommendation algorithm technology in the event network data set is verified, and an algorithm model suitable for marathon event recommendation is obtained. Experiments show that the comprehensive event recommendation model based on term frequency–inverse document frequency (TF-IDF) text weight and Race2vec entry sequence has the best recommendation performance on marathon event data set. According to the recommendation target of the event and the characteristics of the event data type, we can choose a single or comprehensive recommendation algorithm to build a model to realize the event recommendation.

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Providing the minds of the out-of-the-box digitalization as the basic component of the information culture of the teacher

Cited by 3 publications

References 0 publications

Effectiveness of English Online Learning Based on Deep Learning

Effectiveness of English Online Learning Based on Deep Learning

Construction of Enterprise English Adaptive Learning Platform Based on Big Data Analysis

Digitalization and Information Management Mechanism of Sports Events Based on Multisensor Node Cooperative Perception Model

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