Universal Quality Research Articles

Research on the application of neural network modeling in the assessment of traditional sports training and coaches’ quality in colleges and universities

Research on the application of neural network modeling in the assessment of traditional sports training and coaches’ quality in colleges and universities

Construction of Quality Evaluation System for Blended Physical Education Teaching in Colleges and Universities

Abstract The evaluation of the quality of blended physical education teaching in colleges and universities, as a part of the evaluation of university education, is of great significance in guiding the construction and development of blended physical education teaching. This paper examines the evaluation system for hybrid physical education teaching quality in colleges and universities using the principle of evaluation system construction. There are 4 primary indicators, 11 secondary indicators, and 31 tertiary indicators in the system. By using the fuzzy comprehensive evaluation method to calculate the weights of each level 1 index and level 2 index, the weights of each index are judged to account for the proportion. The improved BP neural network algorithm was used to score the indicators. Through empirical analysis, it was found that the weight share of teaching effect, teaching implementation, teaching background, and teaching implementation were 0.33, 0.27, 0.21, and 0.19, respectively, and the teaching effect accounted for the largest share. The total evaluation score was 3.9. The scores of each level indicator in descending order are teaching background (4.13), teaching implementation (4.07), teaching effect (4.05), and teaching setup (3.37). The quality of blended physical education teaching in Colleges and Universities of S is better from the overall point of view.

Evaluation of online teaching quality in colleges and universities based on digital monitoring technology

Evaluation of online teaching quality in colleges and universities based on digital monitoring technology

Evaluation Method of Teaching Reform Quality in Colleges and Universities Based on Big data Analysis

Evaluation Method of Teaching Reform Quality in Colleges and Universities Based on Big data Analysis

Exploring the Teaching Reform of Computer Software Engineering Specialized Courses in Colleges and Universities under the Background of New Engineering Sciences

Abstract The issue of teaching quality in colleges and universities has received widespread attention, and teaching reform using information technology has become a way to improve the quality of university teaching. In this paper, an improvement method is proposed that combines the CBE competency education assessment model and improved C-ADDIE to create a teaching reform model for software engineering courses. After quantitatively assessing students’ professional competence using the IAHP-BP model, students with different competencies are divided by clustering and grouping to analyze the professional competence of software engineering students in terms of the whole and specialty. The professional competence score of the reformed students is 82.103 for the A class students, and the worse performing B class students, the professional competence score is only 72.639, and the gap between the two classes is close to 10 points. After the education of competency assessment with the model proposed in this paper, the student’s professional performance was improved with 11 points in the high score band, and the number of low score bands was gradually reduced. The model developed by the research is a valuable resource for computer software engineering students.

Research on Teaching Quality Monitoring Mechanism of Colleges and Universities Based on Internet+Education Mode

Abstract This paper focuses on the “Internet + education” model and describes the feasible strategy of using data mining technology to establish a teaching quality monitoring mechanism in colleges and universities. Through the study of teaching quality monitoring pathways, such as teachers’ teaching level, students’ academic status, and course learning effectiveness, this paper’s main content provides a directional guide. Based on the teaching quality monitoring pathway, we choose the related algorithms of data mining technology, such as cluster analysis, association rule, and factor analysis, to be applied to the various aspects of the teaching quality monitoring pathway. The clustering algorithm is used to classify 1500 teachers in a university into 4 categories, such as excellent teaching effect, good teaching effect, etc., as well as to cluster students into 6 categories, such as excellent in all the courses and low to medium level, according to the course grades. In addition, this paper analyzes students’ course learning effectiveness, academic level, and career guidance using association rule algorithms, factor algorithms, and decision tree algorithms, respectively. From teachers’ teaching to students’ learning and employment, this paper constructs an all-round teaching quality monitoring mechanism using data mining technology, which contributes to the improvement of teaching quality in colleges and universities.

A comprehensive evaluation of network teaching quality in colleges and universities based on entropy weight TOPSIS model

A comprehensive evaluation of network teaching quality in colleges and universities based on entropy weight TOPSIS model

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.

RETRACTION: Research on Evaluation Method of Physical Education Teaching Quality in Colleges and Universities Based on Decision Tree Algorithm

RETRACTION: Research on Evaluation Method of Physical Education Teaching Quality in Colleges and Universities Based on Decision Tree Algorithm

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.

Analysis and Innovation of Vocal Music Teaching Quality in Colleges and Universities Based on Artificial Intelligence

Abstract The collision between the field of education and the field of artificial intelligence has helped the wisdom reform of college classrooms. At present, traditional vocal music teaching is inefficient and difficult to manage, but it is faced with the dilemma of resource shortage. Therefore, to improve the quality of classroom vocal music teaching in colleges and universities, using innovative thinking, this paper intends to design an artificial intelligence system for evaluating and analyzing classroom effects. Use the test vocal music characteristic parameters for comparison, through the analytic hierarchy process to calculate the quality of the classroom teaching evaluation index, and auxiliary management of the vocal music teaching process. The final simulation results are in line with expectations. It can not only evaluate the whole teaching process reasonably but also help teachers improve the quality of vocal music teaching, which has strong practical value.

A comprehensive evaluation of network teaching quality in colleges and universities based on entropy weight TOPSIS model

A comprehensive evaluation of network teaching quality in colleges and universities based on entropy weight TOPSIS model

Decoding Success: Assessing the Online Pseudocode Interpreter through Users Insights

Pseudocode is vital in enhancing programming comprehension, making it an essential component of the Programming Logic Formulation (CS1) course. However, many CS1 students from various senior high school strands struggle with this concept, highlighting the need for additional learning resources. This research evaluated a pseudocode interpreter designed for first-year Information and Communications Technology (ICT) students at Iloilo Science and Technology University in Iloilo City, Philippines. Using random sampling, 147 first-year ICT students were selected to evaluate the software's user experience in usability, credibility, appearance, and loyalty using the Standardized User Experience Percentile Rank Questionnaire (SUPR-Q). Likewise, five ICT experts were selected using purposive sampling to evaluate the system's validity as instructional material based on its content and on the material's organization, form, and style using the university's Quality Form for Instructional Materials (IM). The user experience evaluation yielded positive results, with students unanimously agreeing on the software's ease of use, dependability, and user-friendliness. The expert evaluation confirmed the system's validity as instructional material, commending its content, organization, form, and style. These findings suggest that the pseudocode interpreter provides immediate benefits for students, offering a valuable learning tool. Moreover, the software has the potential to be adopted by other faculty members, promoting a more efficient and captivating learning experience. Future research could investigate how interpreters affect student learning and their usefulness in various educational settings.

Folklore сomponents of Finnish Rock Poetry

This article explores the folklore components of Finnish rock poetry in Finnish and Swedish. It highlights how Finnish rock culture has revived an ancient tradition where poetry and music were intertwined. While musicians of Amorphis reference “Kalevala” mythology in the songs like “Tuonela”, “Sampo” and “Kantele”, they do not explicitly mention the names of “Kalevala” heroes in their adaptations of runes. The themes of their lyrics seem to take on a universal quality and are set in modern times. The influence of folklore traditions on Finnish authors is evident even in their English-language works. Ville Sorvali of Moonsorrow interprets the runes, trying to understand the intention of their creators, believing that these lyrics resonate with people worldwide. Similarly, Jan Jämsen (Katla), a Swedish-speaking Finn, infuses his native Swedish lyrics for Finntroll with imagery of fantastical creatures and incorporates Sámi folk chants joik to emphasize their uniqueness. Modern Finnish rock poetry stands out for its multilingualism and references to mythological themes from Finnish and Scandinavian folk poetry. However, the resurgence of metrics and imagery from the “Kalevala” and “Kanteletar” in rock poetry was unexpected. Authors use figurative symbolism that may require a deep understanding of Finnish culture to fully appreciate, even in Englishlanguage works. Finnish rock poetry is a diverse and vibrant art form that resonates with universal themes and emotions.

Establishment and Application of Evaluation System for Objective Management of Music and Aesthetic Education Teaching in Colleges and Universities

Abstract Addressing current challenges in music aesthetic education at colleges and universities, this study introduces an evaluation system rooted in hierarchical analysis to advance goal management in teaching. Expert consensus guided the selection and weighting of evaluation indices across a province’s higher education landscape. Implementing this system through information technology and data analysis software, our research analyzed teaching examples to gauge effectiveness. Results demonstrated improved teaching quality, with experimental and control groups showing average score increases of 1.24 and 1.03 points, respectively. This underscores the system’s potential to elevate the management and organization of music aesthetic education, contributing valuable insights to its evaluation theory and enhancing educational quality in Chinese colleges and universities.

Correlation Analysis of Social Terrorism Phenomenon and Psychological Quality in Guangxi Higher Vocational Colleges

Correlation Analysis of Social Terrorism Phenomenon and Psychological Quality in Guangxi Higher Vocational Colleges

Constructing and Empirical Research on Personalized Assessment of English instructors’ instruction quality in Higher Vocational Colleges and Universities

Abstract Personalized assessment of English instructors’ instruction quality is one of the key initiatives to improve the quality of English teaching. This paper proposes an EM-AGA-BP model for English teachers to assess instruction quality. The entropy value method is used for the initial evaluation of English teachers’ teaching quality. The BP neural network is optimized for evaluation learning based on the genetic algorithm of adaptive mutation so as to put forward a more comprehensive and scientific English teachers’ assessment of instruction quality model. At the same time, the English teachers’ instruction quality evaluation index system is constructed. In the empirical analysis, English teachers in colleges and universities are taken as the research object to verify that the assessment of the instruction quality index system by English teachers has better reliability and validity. In the assessment of teaching evaluation quality, English teachers’ evaluation skills are high, with the largest mean value of 4.12, followed by evaluation attitude and evaluation awareness, with mean values of 3.8 and 3.71, respectively, and the overall evaluation score of English teachers’ personalized teaching quality is 3.02, with the evaluation grade level of “medium,” and the evaluation scores of the five evaluation criteria levels are all in the same range. The evaluation scores of the five evaluation criteria layers are all within the score range, and the evaluation level is also “medium.”

Exploration and Reflection on the Development of Internationalized Industry-Education Integration of Vocational Education in the Context of Big Data

Abstract The integration of industry and education serves as a potent mechanism to enhance the educational quality of higher vocational colleges and universities while simultaneously fostering the innovative vitality of enterprises. This study delineates a framework for internationalized industry-education integration in vocational education, grounded in the tripartite relationship among government, enterprises, and educational institutions. Building on this framework, the research initially constructs a performance evaluation index system for internationalized industry-education integration, which encompasses three dimensions: the input, process, and outcomes of industry-education integration. Subsequently, the weights of these indices are determined through hierarchical analysis, and the integration performance of four sample institutions is assessed using fuzzy analysis. The findings reveal that all sampled institutions surpass a ‘good’ performance level, with Institution X1 achieving the highest comprehensive evaluation score of 86.3593. Further, the study conducts an empirical analysis comparing the implementation effects of two models of industry-education integration: the ‘group-run school’ model and the ‘industrial park’ model. The study indicates that the ‘industrial park’ model is marginally superior by 0.13 points in its evaluation compared to the ‘group-run school’ model; however, this difference is statistically insignificant (P>0.05), suggesting that both models exhibit distinct characteristics yet achieve comparable outcomes in integrating industry and education. The research offers actionable insights and practical guidance to advance the development of internationalized industry-education integration within vocational education contexts.

New Approaches to Enhancing Classroom Teaching Quality in Vocational Colleges in the Context of AI Integration

New Approaches to Enhancing Classroom Teaching Quality in Vocational Colleges in the Context of AI Integration

The Application of PDCA Cycle Theory Combined with Subjective and Objective Empowerment Method in Teaching Quality Assessment System of Higher Vocational Colleges and Universities

Abstract As the expansion of higher vocational education hastens the massification of higher education, issues concerning the quality of teaching at higher vocational institutions have become increasingly apparent. This study addresses these concerns by integrating the PDCA (Plan-Do-Check-Act) cycle theory to develop a robust assessment system for evaluating teaching quality in higher vocational colleges. Utilizing a combination of hierarchical analysis and entropy weighting methods, the assessment system is enhanced both subjectively and objectively. By employing higher vocational colleges and universities labeled M1 to M6 as illustrative examples, we apply linear weighted summation to derive comprehensive evaluation scores from the tested teaching quality evaluation index system. The empirical results indicate that the cumulative variance contribution rate of the assessment indices reached 91.765%. In the quality assessment, M4 scored the highest with a composite score of 4.60, while M6 scored the lowest at 3.49. Comparative analysis across dimensions shows that the index scores for M6 were notably lower than those of other institutions, ranging between 3.20 and 3.80. Implementing the proposed teaching quality assurance system resulted in a substantial increase of 0.77 points in its comprehensive score. Thus, the assessment and assurance system developed in this study proves to be practically valuable, offering an effective means to enhance teaching quality and elevate the educational standards in higher vocational colleges.