scholarly journals Exploration on the Teaching Reform Measure for Machine Learning Course System of Artificial Intelligence Specialty

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yizhang Jiang ◽  
Bo Li
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Teaching Quality ◽  
Teaching Reform ◽  
Intelligent Technology ◽  
Quality Evaluation System

Due to the particularity of the artificial intelligence major and the machine learning courses learned, the traditional course teaching model is not suitable for artificial intelligence major machine learning courses. Based on this background, this article proposes a new system based on machine learning curriculum teaching reform. It mainly includes the reform of curriculum teaching mode, curriculum practice reform, and teaching process reform. In order to verify the effect of the proposed new model on the teaching quality of machine learning courses, this article also proposes an evaluation method based on intelligent technology. Firstly, the feasibility of evaluation based on intelligent technology is described. Secondly, it lists the application details of the existing teaching evaluation based on intelligent technology. Finally, a novel teaching quality evaluation system based on intelligent technology is proposed. The system collects student facial expression data and uses classification algorithms to make classification decisions on the data. The result of the decision can give feedback on the quality of classroom teaching. The comparison of experiments based on different intelligent technologies shows that the teaching quality evaluation system proposed in this article is feasible and effective.

Research on Classroom Teaching Quality Evaluation of Chinese as a Foreign Language Based on AHP Model

2013 ◽  
Vol 411-414 ◽  
pp. 2957-2960 ◽  
Author(s):  
Jing Liu
Keyword(s):  
Evaluation System ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Teaching Quality ◽  
Classroom Teaching ◽  
Ahp Model ◽  
Judgment Matrix ◽  
Quality Evaluation System ◽  
Chinese Teaching

How to evaluate the teaching quality of Chinese teacher objectively is an important subject of each university. In view of the shortage of classroom teaching quality evaluation, AHP model is introduced to evaluate the quality of TCFL, and an Chinese teaching quality evaluation system is established. Based on the evaluation content and standard of the system, combined with the the principle of AHP and expert investigation method, a judgment matrix is established, and the weight of each index to the total target is calculated. The comprehensive weight of each index and evaluation object score are multiplied, through a series of calculation, the teachers comprehensive scores can be obtained so as to evaluate the teaching quality. The results show that it is very scientific and objective to evaluate Chinese classroom teaching quality by using AHP model, it is a feasible evaluation method and has higher application value.

An artificial intelligence based model for evaluation of college students’ ability and characteristics through teaching evaluation

2020 ◽  
pp. 1-11
Author(s):  
Bin Li ◽  
Yanying Fei ◽  
Hui Liu
Keyword(s):  
Evaluation System ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Colleges And Universities ◽  
Developmental Potential ◽  
The Core ◽  
Academic Level ◽  
Quality Evaluation System

The teaching quality is the core of sustainable development in colleges and universities. The constructing scientific and reasonable teaching quality evaluation system is the key of teaching quality evaluation. This paper takes the quality of graduates as the core content, establishes a results-oriented teaching quality evaluation system in colleges and universities, and finds that the academic level of graduates and the level of competition in career selection are two quantitative dimensions reflecting the quality of graduates. Based on this, this paper establishes the evaluation model of the developmental potential index and gives the reference of the norm of teaching effect evaluation for self-evaluation. Finally, this paper discusses the components of graduate quality and the way to construct the evaluation system.

Simulation of English teaching quality evaluation model based on gaussian process machine learning

2020 ◽  
pp. 1-11
Author(s):  
Huang Wenming
Keyword(s):  
Machine Learning ◽  
Gaussian Process ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Learning Algorithm ◽  
Teaching Quality ◽  
Distribution Characteristics ◽  
English Teaching ◽  
Traditional Evaluation

The efficiency of traditional English teaching quality evaluation is relatively low, and evaluation statistics are very troublesome. Traditional evaluation method makes teaching evaluation a difficult project, and traditional evaluation method takes a long time and has low efficiency, which seriously affects the school’s efficiency. In order to improve the quality of English teaching, based on machine learning technology, this study combines Gaussian process to improve the algorithm, use mixed Gaussian to explore the distribution characteristics of samples, and improve the classic relevance vector machine model. Moreover, this study proposes an active learning algorithm that combines sparse Bayesian learning and mixed Gaussian, strategically selects and labels samples, and constructs a classifier that combines the distribution characteristics of the samples. In addition, this study designed a control experiment to analyze the performance of the model proposed in this study. It can be seen from the comparison that this research model has a good performance in the evaluation of the English teaching quality of traditional models and online models. This shows that the algorithm proposed in this paper has certain advantages, and it can be applied to the practice of English intelligent teaching system.

scholarly journals Thoughts on the Research of the Multi-evaluation System of the Quality of “Ideological and Political Theories Teaching in All Courses” in Colleges and Universities

2021 ◽  
Vol 3 (3) ◽  
pp. 26
Author(s):  
Lu Xia
Keyword(s):  
Evaluation System ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Evaluation Index ◽  
Political Theories ◽  
Content Evaluation ◽  
Appraisal Method ◽  
Quality Evaluation System ◽  
Evaluation Subject

The teaching quality evaluation system of "Ideological and Political Theories Teaching in All Courses" is far from perfect, as the appraisal content is unitary, and the appraisal method become too rigid. The evaluation system of teaching quality is quite an important mechanism and "baton" to promote the teaching quality of " Ideological and Political Theories Teaching in All Courses ". It has important and realistic research significance to construct a diversified teaching quality evaluation system of " Ideological and Political Theories Teaching in All Courses ". This article focuses on the teaching quality of appraisal content, evaluation subject, appraisal method, and believes that the overall framework of the multi-evaluation system of " Ideological and Political Theories Teaching in All Courses " teaching quality includes multi-evaluation index content, evaluation subject and multi-evaluation methods.

scholarly journals Online Classroom Teaching Quality Evaluation System Based on Facial Feature Recognition

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Fang Yuan ◽  
Yong Nie
Keyword(s):  
Evaluation System ◽  
Quality Evaluation ◽  
Feature Recognition ◽  
Online Courses ◽  
Facial Feature ◽  
Teaching Quality ◽  
Online Classroom ◽  
The Face ◽  
Quality Evaluation System

With the rapid development of computer big data technology, online education in the form of online courses is increasingly becoming an important means of education. In order to objectively evaluate the teaching quality of online classroom, a teaching quality evaluation system based on facial feature recognition is proposed. The improved (MTCNN) multitask convolutional neural network is used to determine the face region, and then the eye and mouth regions are located according to the facial proportion relationship of the face. The light AlexNet classification based on Ghost module was used to detect the open and close state of eyes and mouth and combined with PERCLOS (percentage of eye closure) index values to achieve fatigue detection. Large range pose estimation from pitch, yaw, and roll angles can be achieved by easily locating facial feature angles. Finally, the fuzzy comprehensive evaluation method is used to evaluate students’ learning concentration. The simulation experiments are conducted, and the results show that the proposed system can objectively evaluate the teaching quality of online courses according to students' facial feature recognition.

scholarly journals Application of Optimized GA-BPNN Algorithm in English Teaching Quality Evaluation System

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yaowu Zhu ◽  
Junnong Xu ◽  
Sihong Zhang
Keyword(s):  
Index System ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Teaching Quality ◽  
Model Parameters ◽  
English Teaching ◽  
Comparison Results ◽  
Quality Evaluation System ◽  
Bpnn Model

The assessment of teaching quality is a very complex and fuzzy nonlinear process, which involves many factors and variables, so the establishment of the mathematical model is complicated, and the traditional evaluation method of teaching quality is no longer fully competent. In order to evaluate teaching quality effectively and accurately, an optimized GA-BPNN algorithm based on genetic algorithm (GA) and backpropagation neural network (BPNN) is proposed. Firstly, an index system of teaching quality evaluation is established, and a questionnaire is designed according to the index system to collect data. Then, an English teaching quality evaluation system is established by optimizing model parameters. The simulation shows that the average evaluation accuracy of the GA-BPNN algorithm is 98.56%, which is 13.23% and 5.85% higher than those of the BPNN model and the optimized BPNN model, respectively. The comparison results show that the GA-BPNN algorithm in teaching quality evaluation can make reasonable and scientific results.

scholarly journals Research on the Evaluation Index System and the Grey Clustering Analysis Model of Teaching Quality of Physical Education in Higher Education

2015 ◽  
Vol 10 (8) ◽  
pp. 59 ◽  
Author(s):  
Baoquan Wu
Keyword(s):  
Physical Education ◽  
Clustering Analysis ◽  
Evaluation System ◽  
Quality Evaluation ◽  
Teaching Quality ◽  
Colleges And Universities ◽  
Evaluation Index System ◽  
Analysis Model ◽  
Grey Clustering

Teaching quality evaluation of physical education usually involves multiple influence factors with grey and uncertain information. This brings about limitations to effective evaluation of teaching quality of physical education in colleges and universities. Thus, this paper draws merits from previous research and proposes a teaching quality evaluation system and model of physical education in colleges and universities. First, based on real situations, grey categories of evaluation state for physical education teaching quality are established. The definite weighted functions of grey category of evaluation state are confirmed. Specific steps of the teaching quality evaluation model based on grey clustering analysis are accounted for. Finally, a case study is introduced to verify the model. This model enlightens a new way to evaluate teaching quality of physical education in colleges and universities.

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