Quality Evaluation Model Research Articles

Vocal music curriculum design and teaching quality evaluation in colleges and universities based on interactive structure model

Abstract Aiming at the current phenomenon of low teacher-student interaction in vocal music teaching, this paper combines the interaction structure model for the innovation and practice of college vocal music courses. Then, this paper uses Euclidean distance to improve the binary tree SVM multi-class classification algorithm, calculates the distance between the teaching samples of each vocal music course, classifies the samples for processing, and obtains the DBT-SVM multi-class classification algorithm. Finally, the DBT-SVM algorithm was used to establish an evaluation model for vocal course teaching quality in colleges and universities to assess the quality of vocal course teaching models. Each three-level index of teaching motivationality has an evaluation score above 80, which is a good level. The evaluation score for the pedagogical index is 89.44, which is almost excellent. The average score of the second-level index of interpersonal interaction is 74.52, which needs to be further improved. The teaching model of the college vocal music course proposed in this paper lays the foundation for the interactive transformation of vocal music teaching and provides a reference model for the improvement of the learning effect of college students’ vocal music courses.

Evaluation Method of Teaching Quality of Foreign Language Teachers in Colleges and Universities Based on Decision Tree Algorithm

Abstract Teaching evaluation is an important part of the teaching process in colleges and universities and plays a very important role in the development of higher education and the improvement of education quality. Applying a decision tree algorithm to teaching evaluation can uncover the hidden intrinsic connection between teacher information and course quality evaluation results. This study combines the radar graph with the decision tree C4.5 algorithm to construct a foreign language teaching quality evaluation model, which explores the correlation between teacher information and radar graph attributes on teaching quality evaluation grades on the one hand and evaluates the predictive effect of the model on the other hand. The data mined by the radar chart-C4.5 evaluation model show that if the center of gravity of the radar chart is in the first quadrant, then the evaluation grade passes and has the highest support, which is 53.33%. If the radargram area is large, then the evaluation grade good has the highest confidence level of 77.27%. The evaluation result of the model is that the number of error samples of the prediction grade and the expert evaluation grade are 3 excellent, 5 good, 1 average, 4 qualified, and 1 poor, which proves that the performance of the radar map-C4.5 evaluation model is better.

A construction of online teaching quality evaluation model based on big data mining

A construction of online teaching quality evaluation model based on big data mining

Automatic Machine Translation Quality Evaluation Model under Feature Extraction Algorithm

Automatic Machine Translation Quality Evaluation Model under Feature Extraction Algorithm

Research on Quality Grading Evaluation and Performance Prediction of Construction Waste Recycled Materials

The application of construction waste in road engineering is an effective means to improve the level of resource recycling. Due to the lack of specialized sorting equipment for different types of construction waste and the high cost of manual sorting, resource utilization enterprises mainly rely on mixed crushing and regeneration in production, while there is a lack of systematic research on the application technical indicators of recycled aggregates for brick concrete mixed construction waste. This article proposes a quality evaluation model for construction waste coarse aggregates based on the theory of matter element extension, providing new ideas for quantitative evaluation of the quality status of coarse aggregates, and also providing reference for the rational selection of recycled coarse aggregates and the determination of mechanical parameters of coarse aggregates in the construction process, which is conducive to the evaluation and analysis of the quality status of recycled coarse aggregates.

A Construction of online teaching quality evaluation model based on big data mining

A Construction of online teaching quality evaluation model based on big data mining

Research on Teaching Quality Evaluation Model of Higher Mathematics Based on Hierarchical Analysis Approach

Abstract The teaching quality of higher mathematics courses plays a pivotal role in the cultivation of students’ quality and the improvement of their abilities. In this paper, information entropy is added to the hierarchical analysis method to improve it and then combined with the fuzzy synthesis method to construct a model for evaluating the quality of mathematics teaching. The higher mathematics teaching course at a university is selected as the research object, and the constructed model for evaluating the quality of higher mathematics teaching is applied to the teaching of higher mathematics in classrooms. The evaluation index system for higher mathematics teaching quality is established by combining relevant literature, and the improved AHP is used for weighting. Then, the index data is collected through questionnaires to analyze the differences and assess the teaching quality of different genders and majors and then to propose strategies to improve the teaching quality of higher mathematics. The significant effects of teaching methods (0.184), teaching effectiveness (0.176), and teaching content (0.170) on the teaching quality of higher mathematics were revealed. The quality of teaching higher mathematics in the sample universities is located at a good level with scores between 8 and 9 on each evaluation index, with the best performance of 8.934 for teaching content. The evaluation model for higher mathematics teaching quality established by the research has validity and feasibility.

A Study on Data-Driven Cluster Analysis of Teaching Quality in Civic and Political Education in Colleges and Universities

Abstract The implementation of teaching quality evaluation has a certain guiding effect on a series of teaching works, such as teaching reform and teaching management, and the selection of appropriate evaluation methods is very important for the implementation of teaching quality evaluation. In this study, the hierarchical analysis method and K-means clustering algorithm were used to construct and assess a teaching quality evaluation model for college Civics education. Prior to evaluating the teaching quality of Civic and political education in colleges and universities, the hierarchical structure model and index system were established using the hierarchical analysis method. Then, the K-means clustering algorithm is utilized to execute the data mining work to assess the quality of data-driven teaching through clustering. The algorithm’s purity and F1 values are 0.895 and 0.834, respectively, and it performs well in clustering. Finally, the clustering analysis of the teaching quality of college civic education was conducted. The final scores of teaching quality, teaching method, teaching content, teaching effect, and teaching characteristics accounted for 98.28%, 87.76%, 88.03%, 71.4%, and 83.2% of the total scores of each, respectively. All the scores are in the middle of the range, indicating that the overall teaching situation is in the middle of the range with better results. The purpose of this study is to provide lessons and references for cluster analysis of civic education teaching quality in colleges and universities.

Quality Evaluation Model of Innovation and Entrepreneurship Education Based on Intelligent Genetic Algorithm under Virtual Reality Technology

Quality Evaluation Model of Innovation and Entrepreneurship Education Based on Intelligent Genetic Algorithm under Virtual Reality Technology

Introduction to the inheritance and development of national music culture in the teaching of music education in colleges and universities in the Internet era

Abstract Ethnic music culture is a rare and precious artistic treasure in all national cultures, and the inheritance and promotion of ethnic music culture is an essential part of music education teaching in colleges and universities. This paper delves into the characteristics of the development and dissemination of ethnic music culture in the Internet era, with the aim of studying the integration of ethnic music culture into music education teaching in colleges and universities through the use of Internet technology. Through the collaborative filtering algorithm, students’ preferences for ethnic music works are mined so as to recommend accurate teaching resources for college students on the ethnic music online teaching platform constructed based on the collaborative filtering algorithm. In order to fully prove the effectiveness of the teaching platform designed in this paper, the rough set theory and neural network algorithm are used to construct the online teaching quality evaluation model for college ethnic music. The questionnaire survey method is used to study the status quo of ethnic music teaching in colleges and universities, and it is concluded that at present, there are problems in ethnic music teaching in colleges and universities, such as insufficient concepts of students learning ethnic music and insufficient attention to ethnic music in colleges and universities themselves. Through the analysis of the effect of the recommended algorithm, the design of the evaluation index system, and the practical application, the quantitative assessment value of the teaching quality of the ethnic music online teaching platform designed in this paper in the practical application is 92.11, which indicates that the comprehensive rating of the quality of the ethnic music online teaching in colleges and universities in this paper is excellent.

Intelligent Monitoring of Data Quality Based on Multiple Data Structures

In the current context of big data, data quality management has become a hot topic in data science research. This article focused on the intelligent monitoring needs of complex data structures and explored data quality evaluation indicators and monitoring methods for complex environments. Key technologies such as data fusion, cleaning, and quality evaluation were focused on research, and a data quality monitoring system for multi-dimensional data environments was constructed to verify its application effectiveness in multi-source data environments, as well as specific measures to improve data quality. On this basis, a data quality evaluation model based on data mining was utilized, and a real-time monitoring system was established for application research. When the number of consistency issues was 30, the response time was 300ms, and the success rate of processing was 95%. The lowest processing success rate was 88%, and the highest was 100%. The overall processing success rate of the system was very good. The research results of this article provided theoretical and methodological support for enterprises to effectively carry out data quality management, which has important theoretical significance and application value.

A Quality evaluation model of distance assisted instruction based on AHP and entropy weight method

A Quality evaluation model of distance assisted instruction based on AHP and entropy weight method

A quality evaluation model of distance assisted instruction based on AHP and entropy weight method

A quality evaluation model of distance assisted instruction based on AHP and entropy weight method

Research on quality evaluation model of IUD based on machine learning algorithm

Research on quality evaluation model of IUD based on machine learning algorithm

Innovation of Student Quality Evaluation Model in Vocational Education under Cloud Computing Environment

Abstract This paper takes cloud computing technology as the core, constructs a student quality evaluation model, collects and analyzes students’ learning data through cloud computing technology, proposes the direction of optimization and reform of the educational quality evaluation system, and establishes a comprehensive quality evaluation management system for students. Combining AHP and entropy weight methods, the subjective and objective weights of each index are calculated, and the comprehensive weights are determined through game theory. Based on the evaluation method of students’ comprehensive quality, the cloud model is established, the normal cloud digital features are calculated, and the mapping of qualitative concepts to quantitative representations is realized through the forward cloud generator, which completes the construction of the evaluation index system of students’ comprehensive quality. The evaluation cloud model is obtained by using the digital features calculation, and the cloud is located between levels 8 and 9 because E x = 8.5265, which has a closer fit with level 8, indicating that the comprehensive quality of the student belongs to the good upper level. In the comparison of the innovation of the student quality evaluation model, the comprehensive theoretical quality of the students in the experimental group is 8.215 points, and the P value is 0, significantly higher than that of the control group students, and the model innovation effect is remarkable.

Implementation Mechanism of Industry-Education-Creation Mixed Ownership Industrial College Based on AHP Fuzzy Evaluation Model

Abstract The management of modern industrial colleges is the deepening and developing the fusion of industry-teaching-creation and school-enterprise cooperation talent cultivation mode, which has strategic height and practical significance. This paper establishes the evaluation index system of the implementation mechanism of industrial colleges based on BSC theory. It creates the implementation mechanism model of mixed teaching and learning in industrial colleges. Combining qualitative and quantitative analysis, the hierarchical and fuzzy hierarchical analysis methods are used to construct the hybrid teaching quality evaluation model of industry-teaching-creation. Then the weights of the evaluation indexes of the implementation mechanism of industrial colleges are calculated. The industrial colleges of college A and college B are selected as the research objects to comprehensively evaluate the implementation effect of their mixed industry-teaching-creation teaching. The optimal model is determined by calculating the comprehensive scores of the five industry-education-creation hybrid teaching implementation mechanisms. The study shows that the highest weight of finance is 0.333. The total scores of college A and B are 80.56 and 83.33, and college B has a higher level of industry-teaching-creation hybrid teaching implementation mechanism. The composite score of the co-constructed science and technology park model is 0.233, the optimal mixed teaching implementation mechanism of Industry, education and creativity.

Optimization of the path of industry-teaching integration in vocational education based on ADDIE model

Abstract The integration of industry and education plays a vital role in the high-quality development of vocational education. The article adopts the ADDIE model to systematically design vocational education and plans the path of industry-education integration by combining the triple helix theory. In addition, a quality evaluation model for integrating industry and education in vocational education is constructed, connecting the fuzzy comprehensive evaluation method and the factor analysis method. The empirical Analysis shows that the extensive evaluation indexes of vocational education have high reliability (more than 0.8), in which there is a positive correlation between teaching ability, teaching management, teaching effect and employability. In particular, the comprehensive effectiveness evaluation score of School M in the practice of industry-teaching integration in vocational education is 4.125, showing a reasonable level. The study verifies the effectiveness of the vocational education industry-education integration model based on the triple helix theory in improving the quality of education, and at the same time provides a scientific basis for the optimization and reform of the path of vocational education industry-education integration.

3D Animation Production and Generation Based on Human Body Base 3D Models

Abstract With the gradual increase in the demand for parametric human 3D models, the requirements for the accuracy of modeling and the quality of generation are getting higher and higher. In this paper, the human body structure model is constructed by 3D human posture estimation and spatio-temporal graph convolutional network, and after normalizing the data of the human body base, the 3D human body model based on the human body base is generated by combining the free deformation method, and the local light model is used to make the human body model more three-dimensional and real. In addition, the quality of 3D animation production is investigated by combining blind quality evaluation and validation analysis of the human body-based 3D model. The 3D human body modeling simulation error assessment has an error assessment root-means-square error that falls within 1.5%. In the validation analysis of model generation quality, the quality evaluation model proposed in this paper has a quality correlation coefficient and prediction accuracy of 0.9456 and 0.9454 on the dataset, respectively, and the performance of the ablation experiments and generalization experiments is stable. The mean value of the error between the animation production character generation effect and the actual testers is not more than 10mm.Combined with the research in this paper, it effectively improves the accuracy of human body modeling and provides an evaluation method for the quality of human 3D animation production and generation, which is of practical significance for its development.

Construction of an information-based English teaching quality evaluation system based on the fusion of multimedia English educational resources

Abstract Today's information technology is constantly evolving, multimedia teaching, a new form of classroom teaching, has long been widely used by colleges. However, in many colleges, its teaching advantages have not been fully exerted, although the school spends a lot of human, data, and financial resources to publicize and promote multimedia classroom teaching, the effect of multimedia classroom teaching is not very good. There are many reasons for this, including the lack of an effective evaluation system to guide teachers in their teaching activities. Therefore, the top priority is Establishing a correct and appropriate multimedia English teaching evaluation index system. Starting from the characteristics and requirements of multimedia classroom teaching, this paper constructs a multimedia classroom teaching evaluation index system in colleges and universities based on the problems faced by current multimedia classroom teaching, promoting the quality of teaching in multimedia English classrooms through the English Teaching Evaluation System - the medium between theory and practice. The teacher teaching quality evaluation system studied in the thesis can completely solve the problem of unreasonable evaluation of teacher learning quality, and provide an integrated teaching quality evaluation model for students, teachers, and academic affairs offices. The system has changed the original evaluation method and constructed a teaching quality evaluation model that integrates. Data collection, evaluation management, online evaluation, and teaching resource data management, to achieve fair, scientific, and comprehensive evaluation, and provide a comprehensive management and analysis platform for comprehensively mastering evaluation of multimedia English teaching quality.

Design and Innovative Methods of English Teaching Tutorials in the Context of the Information Age

Abstract In this work, the problem of teaching English in colleges and universities throughout the information age is addressed by using augmented reality (AR) technology to finish designing the teaching activities and objectives. It establishes the English teaching evaluation index system, uses the Hummingbird optimization algorithm to optimize the convolutional neural network’s parameters, and builds the English teaching quality evaluation model based on this optimization. We assess students’ happiness and their capacity for autonomous learning in English instruction in the information era by statistical analysis, and we investigate novel approaches for English teaching tutorials in the information age. The results show that, in terms of overall satisfaction with English teaching, freshmen students have the highest level of satisfaction with the three phases of English teaching, with values of 216.71, 215.36, and 218.13, and sophomores have the lowest level of satisfaction, with values of 137.41, 133.01, and 138.76, indicating that there is a difference in student satisfaction by grade level. Establishing goals and monitoring the use of strategies were highly correlated with teacher support (P=0.534, 0.554 >0.5), which indicates a significant correlation between teacher support and students’ ability to learn English independently. This study can have a positive impact on the creative impact of teaching English in colleges and universities and successfully promote innovative transformation of the teaching mode.