Smart teaching evaluation model using weighted naive bayes algorithm

2020 ◽  
pp. 1-11
Author(s):  
Lin Liu
Keyword(s):  
Machine Learning ◽  
Evaluation System ◽  
Evaluation Model ◽  
Evaluation Process ◽  
Teaching Quality ◽  
Teaching Evaluation ◽  
Current Status ◽  
Basic Algorithm ◽  
Model Training ◽  
Bayes Algorithm

There is a certain subjectivity in the teaching evaluation process, which leads to a low accuracy of the intelligent scoring system. In order to promote the intelligent development of teaching evaluation, based on machine learning, this study briefly introduces the background and current status of teaching evaluation, and describes in detail the relevant algorithm principles of data analysis and modeling using data mining technology and machine learning methods. Moreover, this study describes the establishment process of the traditional classroom teaching evaluation system and uses the classification algorithm in machine learning in the construction of evaluation models to further improve the scientificity and feasibility of teaching evaluation. In addition, in this study, empirical algorithm is used as the basic algorithm to evaluate teaching quality, and the topic word distribution obtained by joint model training is used as the original knowledge. Finally, this research analyzes the performance of this research system through a control experiment. The research results show that the scores of the research model are close to the standard manual scores and can provide a theoretical reference for subsequent related research.

Study on English Teaching Evaluation System in Higher Vocational Colleges

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Yanhong Zhao
Keyword(s):  
International Education ◽  
Evaluation System ◽  
Evaluation Process ◽  
Teaching Quality ◽  
Teaching Evaluation ◽  
Point Of View ◽  
Strategic Choices ◽  
English Teaching ◽  
Stage Of Development ◽  
Vocational Colleges

<p><em>After decades of development, vocational education in our country has gradually entered a new stage of development and is faced with new opportunities for development and strategic choices. Especially in the 21st century, the domestic demand for skilled professionals increases year by year. Under such circumstances, how to further optimize the teaching system of higher vocational colleges and strengthen the guidance and management has become an urgent need for education. </em><em>English</em><em> </em><em>curriculum</em><em>, </em><em>as an international education course, are the key steps f</em><em>or students to learn foreign cultures, touch new things and go to the world stage. The quality of teaching is inextricably linked with English teaching evaluation system. </em><em>The article</em><em>,</em><em> from the overall point of view</em><em> and </em><em>the part of the higher vocational colleges </em><em>,</em><em> fully</em><em> </em><em>elaborat</em><em>es </em><em>English teaching evaluation system</em><em>;</em><em> </em><em>and</em><em> analy</em><em>zes </em><em>the problems in the evaluation process, </em><em>as well as </em><em>the actual situation in major vocational colleges </em><em>and puts forward </em><em>the establishment of appropriate</em><em> </em><em>English teaching evaluation system for the purpose of</em><em> </em><em>improv</em><em>ing</em><em> teaching quality</em><em> and </em><em>train</em><em>ing</em><em> more English professionals to meet the needs of society and the country.</em><em></em></p>

scholarly journals Teaching Evaluation System by use of Machine Learning and Artificial Intelligence Methods

2021 ◽  
Vol 16 (05) ◽  
pp. 87
Author(s):  
Jingjing Hu
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Classification Accuracy ◽  
Evaluation System ◽  
Learning Algorithm ◽  
Evaluation Model ◽  
Teaching Evaluation ◽  
Bp Algorithm ◽  
Machine Learning Algorithm ◽  
Existing Problems

To explore the adoption of artificial intelligence (AI) technology in the field of teacher teaching evaluation, the machine learning algorithm is proposed to construct a teaching evaluation model, which is suitable for the current educational model, and can help colleges and universities to improve the existing problems in teaching. Firstly, the existing problems in the current teaching evaluation system are put forward and a novel teaching evaluation model is designed. Then, the relevant theories and techniques required to build the model are introduced. Finally, the experiment methods and process are carried out to find out the appropriate machine learning algorithm and optimize the obtained weighted naive Bayes (WNB) algorithm, which is compared with traditional naive Bayes (NB) algorithm and back propagation (BP) algorithm. The results reveal that compared with NB algorithm, the average classification accuracy of WNB algorithm is 0.817, while that of NB algorithm is 0.751. Compared with BP algorithm, WNB algorithm has a classification accuracy of 0.800, while that of BP algorithm is 0.680. Therefore, it is proved that WNB algorithm has favorable effect in teaching evaluation model.

scholarly journals Construction of Music Teaching Evaluation Model Based on Weighted Naïve Bayes

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiongjun Xia ◽  
Jin Yan
Keyword(s):  
Evaluation System ◽  
Naive Bayes ◽  
Evaluation Model ◽  
Audio Signal ◽  
Naïve Bayes ◽  
Teaching Evaluation ◽  
Machine Learning Algorithms ◽  
Music Teaching ◽  
Model Based ◽  
Bayes Algorithm

Evaluation of music teaching is a highly subjective task often depending upon experts to assess both the technical and artistic characteristics of performance from the audio signal. This article explores the task of building computational models for evaluating music teaching using machine learning algorithms. As one of the widely used methods to build classifiers, the Naïve Bayes algorithm has become one of the most popular music teaching evaluation methods because of its strong prior knowledge, learning features, and high classification performance. In this article, we propose a music teaching evaluation model based on the weighted Naïve Bayes algorithm. Moreover, a weighted Bayesian classification incremental learning approach is employed to improve the efficiency of the music teaching evaluation system. Experimental results show that the algorithm proposed in this paper is superior to other algorithms in the context of music teaching evaluation.

scholarly journals Construction practice of student evaluation system based on JFinal + webix integrated framework and Baidu AI platform

2021 ◽  
Vol 336 ◽  
pp. 05016
Author(s):  
Zhan Gao ◽  
Zhihai Suo ◽  
Jun Liu ◽  
Mo Xu ◽  
Dandan Hong ◽  
...  
Keyword(s):  
Evaluation System ◽  
Student Evaluation ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Integration Framework ◽  
Online Student ◽  
Evaluation Of Teaching ◽  
Multi Level ◽  
Level Student ◽  
Construction Practice

Students' evaluation of teaching is a key link to realize teaching quality monitoring and promote teachers' teaching level. Based on the practice of student evaluation in our university, this paper constructs a multi-level student evaluation system, and develops an online student evaluation system by using JFinal+webix integration framework. The new Internet plus evaluation model is established to improve the efficiency of student evaluation and the enthusiasm of students to evaluate teaching. Meanwhile, based on the analysis of students' comments on teaching by Baidu AI platform, It provides data support for the improvement of learning level and the optimization of teaching evaluation.

scholarly journals Responsive Dashboard as a Component of Learning Analytics System for Evaluation in Emergency Remote Teaching Situations

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 7998
Author(s):  
Emilia Corina Corbu ◽  
Eduard Edelhauser
Keyword(s):  
Online Education ◽  
Learning Analytics ◽  
Evaluation System ◽  
Online Courses ◽  
Evaluation Model ◽  
Evaluation Process ◽  
Educational Process ◽  
Study Objective ◽  
Teachers And Students ◽  
The Evaluation System

The pandemic crisis has forced the development of teaching and evaluation activities exclusively online. In this context, the emergency remote teaching (ERT) process, which raised a multitude of problems for institutions, teachers, and students, led the authors to consider it important to design a model for evaluating teaching and evaluation processes. The study objective presented in this paper was to develop a model for the evaluation system called the learning analytics and evaluation model (LAEM). We also validated a software instrument we designed called the EvalMathI system, which is to be used in the evaluation system and was developed and tested during the pandemic. The optimization of the evaluation process was accomplished by including and integrating the dashboard model in a responsive panel. With the dashboard from EvalMathI, six online courses were monitored in the 2019/2020 and 2020/2021 academic years, and for each of the six monitored courses, the evaluation of the curricula was performed through the analyzed parameters by highlighting the percentage achieved by each course on various components, such as content, adaptability, skills, and involvement. In addition, after collecting the data through interview guides, the authors were able to determine the extent to which online education during the COVID 19 pandemic has influenced the educational process. Through the developed model, the authors also found software tools to solve some of the problems raised by teaching and evaluation in the ERT environment.

scholarly journals Application of Analytical Hierarchy Process in Teaching Quality Analysis of English Writing

2020 ◽  
Vol 15 (14) ◽  
pp. 137
Author(s):  
Xiaoqin Zhang ◽  
Shengxin Wang ◽  
Yanling Cao ◽  
Guangqi Chen
Keyword(s):  
Analytical Hierarchy Process ◽  
Evaluation System ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Quality Analysis ◽  
English Writing ◽  
Evaluation Systems ◽  
Hierarchy Process

There are two major problems in the evaluation of the teaching quality of English writing: the weak logic of the evaluation system and the low reliability of the evaluation model. To solve the problems, this paper put forward an evaluation method for the teaching quality of English writing based on the analytical hierarchy process (AHP). Firstly, the authors reviewed the current evaluation methods for the teaching quality of English writing. Next, hierarchical evaluation systems were established for the teaching quality of English writing from the perspectives of teachers and students, respectively. After that, the AHP method and the grey theory were introduced to set up an evaluation model for the teaching quality of English writing. Finally, several strategies were presented to improve the teaching quality of English writing. The proposed evaluation systems and model enriched the theories on teaching quality evaluation of English writing, and promoted the teaching quality of English writing.

The Application of Fuzzy Comprehensive Evaluation Model in the Teaching Evaluation System

2013 ◽  
Vol 303-306 ◽  
pp. 1452-1455 ◽  
Author(s):  
Shu Wen Sun ◽  
Yu Wen Zhai
Keyword(s):  
Evaluation System ◽  
Online Teaching ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Teaching Evaluation ◽  
Comprehensive Evaluation Method ◽  
Time Control ◽  
Control Change

According to the subjectivity, randomness and fatigue of the satisfaction selection of online teaching evaluation indicators for the students, the level of teachers teaching can not truly measure by the evaluation results. This paper introduces the fuzzy comprehensive evaluation method to deal with the evaluation data, and Practice has proved that this method produced results more equitable to reflect on teaching level. Which help teachers to promptly improve and improve teaching, the variable quality of teaching time control for process control, change the static management for dynamic management.

Research on Comprehensive Evaluation of Service Capability of the Third-Party Logistics Suppliers with AHP and Gray Entropy Theory

2021 ◽  
Author(s):  
Jun Li ◽  
Xuhua Pan ◽  
Mingxiao Li ◽  
Gang Wang ◽  
Zhixin Zhang
Keyword(s):  
Evaluation System ◽  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Evaluation Process ◽  
Third Party ◽  
Third Party Logistics ◽  
Comprehensive Service ◽  
Service Capability ◽  
Capability Evaluation

To solve the problem of third-party logistics (3PL) evaluation and selection, a hybrid method with AHP and gray theory is proposed. First, the literature review about the 3PL evaluation method and technology is introduced. Furthermore, TPL comprehensive service capability evaluation system is established from aspects of service, time, cost and enterprise qualification. Besides, a comprehensive evaluation model process with gray entropy and AHP is introduced. Finally, a detailed evaluation process of 3PL supplier service capability in F company is introduced by an example, and the results show that the evaluation method in the paper is helpful to choose the TPL for logistics outsourcing.

scholarly journals Research on Teaching Model of Medical Information Retrieval

2018 ◽  
Vol 227 ◽  
pp. 03003
Author(s):  
Yongrui Zhang ◽  
Jialin Gao
Keyword(s):  
Information Retrieval ◽  
Evaluation System ◽  
Medical Information ◽  
Classroom Interaction ◽  
Teaching Quality ◽  
Current Status ◽  
The Internet ◽  
Teaching Model ◽  
Traditional Teaching ◽  
Medical Information Retrieval

With the advent of the Internet era, traditional teaching forms, teaching methods and teaching concepts have undergone tremendous changes, and the teaching of medical information retrieval courses has also undergone good changes. This paper will explore the new teaching model of medical information retrieval under the Internet era from the teaching modes of PICOS, MOOC, SPOC, etc., in order to change the current status of poor classroom interaction and lack of high-quality teaching resources in college medical information retrieval courses, and improve the teaching quality of medical information retrieval courses and graduate students’ information literacy; and effectively change the traditional teaching evaluation system, give full play to the advantages of the network environment, and better innovate and rectify the teaching mode of medical information retrieval courses.

scholarly journals Study on College English Online Teaching Model in Mixed Context Based on Genetic Algorithm and Neural Network Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Xiaoxia Ma
Keyword(s):  
Neural Network ◽  
Online Teaching ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Teaching Evaluation ◽  
Variation Method ◽  
Classroom Teaching ◽  
Evaluation Report ◽  
College English ◽  
English Classroom

College English classroom teaching evaluation is an important basis for understanding teaching level and improving teaching quality. The traditional college English classroom teaching evaluation is mainly carried out through questionnaires and scales, but this method is time-consuming and laborious, inevitably introduces subjective errors, and reduces the accuracy and credibility of the evaluation results. In recent years, the rise and development of wisdom education not only provides a more convenient and efficient modern education form but also brings new ideas for classroom teaching evaluation. A subjective and objective fusion statistical evaluation model based on multidirectional genetic variation method and optimized neural network is proposed. The algorithm avoids subjective errors and improves the accuracy and reliability of the evaluation results, and a comprehensive evaluation model is constructed. Finally, according to different evaluation indexes, a systematic visualization scheme is designed to generate students’ classroom learning evaluation report and teachers' classroom teaching evaluation report, respectively, and visualize them on the web.

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