Research on formative moral education evaluation model of online learners based on data driven

Author(s):  
Ji Yanli ◽  
Gao Dayong ◽  
Liu Yong
2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Xiaolin Yuan

Contemporary young college students are greatly impacted in the aspects of moral cognition and moral choice, which results in the weak moral will of some college students, vague moral concepts, and weak ideals and beliefs, which seriously affect the formation and development of college students’ moral quality. Therefore, the moral education evaluation model based on college students’ quality cultivation is constructed. Firstly, the present situation and defects of college students’ quality training are analyzed. Based on this, association rules in data mining method are constructed and introduced to extract valuable knowledge hidden in the data to assist education managers to make effective decisions and improve management level. Finally, the evaluation index is selected and the weighted principal component TOP-SIS model is constructed to realize the evaluation of moral education based on college students’ quality cultivation. The experimental results show that the evaluation results of the model are consistent with the actual situation, high degree of fit and freedom, and good practical performance.


1978 ◽  
Vol 1 (4) ◽  
pp. 265-272 ◽  
Author(s):  
John C. Ory ◽  
Zelema Harris ◽  
Sue B. Dueitt ◽  
Donald L. Clark

Author(s):  
M S Hasibuan ◽  
L E Nugroho ◽  
P I Santosa ◽  
S S Kusumawardani

A learning style is an issue related to learners. In one way or the other, learning style could assist learners in their learning activities if students ignore their learning styles, it may influence their effort in understanding teaching materials. To overcome these problems, a model for reliable automatic learning style detection is needed. Currently, there are two approaches in detecting learning styles: data driven and literature based. Learners, especially those with changing learning styles, have difficulties in adopting these two approach since they are not adaptive, dynamic and responsive (ADR). To solve the above problems, a model using agent learning approach is proposes. Agent learning involves performing activities in four phases, i.e. initialization, learning, matching and, recommendations to decide the learning styles the students use. The proposed system will provide instructional materials that match the learning style that has been detected. The automatics detection process is performed by combining the data-driven and literature-based approaches. We propose an evaluation model agent learning system to ensure the model is working properly.


2020 ◽  
Vol 309 ◽  
pp. 02017
Author(s):  
Yicheng Gong ◽  
Juan Zhao ◽  
Dongyang Zhang

The traditional comprehensive evaluation is difficult to model when dealing with large data with large parameters and complex structure, and it cannot adapt to the update of data. In order to improve this situation, this paper draws on the Adaptive Learning Adaboost perspective in statistical learning to develop a data-driven integrated evaluation model that updates the weight of sample weights and weak evaluation models with data. Three specific weak evaluation models were selected: data-driven Topsis method, principal component analysis method and factor analysis method. Taking the ranking of WeChat public account as an example, the results show that the accuracy of the integrated evaluation model is 88.57%, which is 17.14%, 31.43% and 28.57% higher than the data-driven Topsis method, principal component method and factor analysis method.


Technovation ◽  
2018 ◽  
Vol 72-73 ◽  
pp. 1-12 ◽  
Author(s):  
Heeyong Noh ◽  
Ju-Hwan Seo ◽  
Hyoung Sun Yoo ◽  
Sungjoo Lee

2014 ◽  
Vol 926-930 ◽  
pp. 4457-4460
Author(s):  
Yin Zhen Zhong ◽  
Min Xia Liu ◽  
Wei Chun Gao

In order to improve the credibility of vocational teaching evaluation, the paper summarizes the traditional SEEQ evaluation model, and analyzes some existing deficiencies. Combined with the demand of current teaching evaluation, a kind of improved teaching evaluation model-VSEEQ is proposed. The model increases two new evaluation dimensions. Through the research sampling, the data is conducted the KMO and Bartlett analysis. The experiment can show that VSEEQ evaluation result can accurately reflect the practical issue existed in the teaching, thus greatly improving the credibility of teaching assessment.


2021 ◽  
Vol 336 ◽  
pp. 08014
Author(s):  
Zhaosheng Xu

in this paper, we construct a data-driven trust evaluation model based on perceptual source. The model takes the monitoring module as the evaluation unit, and the relay node completes the trust evaluation of the sensing node in its monitoring module. The direct trust calculation is realized by the relationship between the sensing node's own data, and the recommended trust is calculated by using the relationship between the neighbor nodes in the monitoring module. Combined with the historical trust, the comprehensive trust of the sensing node is output. In this paper, the credibility of existing database driven cognitive software is summarized, and then the key technologies of reliability evaluation and classification of database driven cognitive software are analyzed.


2018 ◽  
Vol 88 ◽  
pp. 13-22 ◽  
Author(s):  
Wei Zhang ◽  
Zhihui Lu ◽  
Ziyan Wu ◽  
Jie Wu ◽  
Huanying Zou ◽  
...  

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