Teaching Quality Evaluation Research Articles

Design of Oral English Teaching Quality Evaluation System Based on AHP-Fuzzy Algorithm

In the evolving landscape of English oral language instruction, the integration of online and offline (blended) teaching methodologies has emerged as a significant approach to enhance learning outcomes. This study addresses the need for a robust and nuanced evaluation framework capable of assessing the quality of blended English oral language teaching. Motivated by the limitations of traditional evaluation methods in capturing the complexities and subjective nuances of blended teaching environments, we propose a novel evaluation model that leverages the Analytic Hierarchy Process (AHP) and Fuzzy Association Analysis. This paper outlines a systematic approach to construct a comprehensive evaluation indicator system tailored to the specific demands of English oral language teaching. Utilizing AHP, we determine the relative weights of various evaluation indicators, laying a solid foundation for a structured assessment framework. Subsequently, Fuzzy Association Analysis is employed to handle the inherent uncertainties and subjectivities associated with teaching quality assessment, thereby facilitating a more accurate and holistic evaluation. An empirical case study is presented to demonstrate the practical application of our proposed AHP-Fuzzy model in evaluating the quality of a specific blended English oral language teaching program. The results underscore the model’s effectiveness in providing a detailed and nuanced assessment of teaching quality, highlighting its superiority over traditional evaluation methods in addressing the complexities of blended teaching environments.

Dynamic Modeling Analysis of University Physical Education Teaching Quality Evaluation System Under Big Data

With the rapid development of internet technology, the importance of data in various industries has become increasingly prominent. However, in the field of domestic education, especially the research on teaching quality evaluation is relatively sparse. This paper aims to build an evaluation model of physical education teaching quality with big data and machine learning in order to comprehensively evaluate teachers' physical education teaching ability. Firstly, a multi-dimensional evaluation system is designed to measure teachers' teaching level. Secondly, through the questionnaire and the statistical analysis of students' physical education teaching evaluation, the availability of the college physical education teaching evaluation system is verified. On this basis, a teacher's ability prediction model based on a neural network is established, and the experimental results show that the prediction accuracy of the model is 90.17%. This provides strong support for improving the quality of physical education teaching.

Research on Interactive Higher Education Quality Evaluation Model based on Affective Input Computing Framework

Research on Interactive Higher Education Quality Evaluation Model based on Affective Input Computing Framework

Self-Assessment Guide to Quality in Accessible Virtual Education: An Expert Validation

The evaluation of quality in education has gained greater relevance, especially after the COVID-19 pandemic, which enhanced virtual learning and further highlighted the need for inclusive, equitable, and quality education in line with SDG 4. It has become indispensable to have evaluation models and tools supported by empirical validation to ensure their applicability and reliability in diverse educational contexts. This study addresses this need by validating a self-assessment guide designed to evaluate the quality of virtual education from an accessibility perspective. The validation process involved three phases: a preliminary phase with 4 experts to identify areas for improvement in the structure, clarity, and relevance of the content; an extended phase with 20 experts to evaluate reliability and validity; and a pilot study implemented in four higher-education institutions to verify the guide’s applicability in real environments. Reliability and validity were assessed using standard psychometric techniques, confirming high internal consistency and content validity, although some areas required clarity adjustments. The findings indicate that this guide can serve as a robust tool for institutions aiming to advance accessible and high-quality virtual education, directly supporting SDG 4’s commitment to inclusive education.

Assessing the students’ evaluations of educational quality (SEEQ) questionnaire in Oman higher education

Background One of the most popular tools that is used to evaluate education quality is the Student Evaluation of Education Quality (SEEQ). This local data study examined the SEEQ’s psychometric properties in Omani education, specifically its validity and reliability. Methods This was quantitative research to assess educational quality from the students’ viewpoint. The study was conducted at Muscat College from January to March 2024.Simple randomization implemented at the course level helped to choose the participants. All students registered in the specified courses were asked to take part after a random sample of the courses Muscat College offers throughout the study term was chosen. Five hundred fifty students completed the survey. AMOS was used to conduct confirmatory factor analysis (CFA), and PSS was used to evaluate the internal consistency (IBM Corp., 2024a, 2024b). Results CFA of the SEEQ indicated that the eight -factor solution best fit the data. Results also showed that the SEEQ has overall good-to-excellent reliability. The adapted scale was psychometrically sound, proving SEEQ’s applicability Conclusions This study proposes using SEEQ to measure Oman’s education quality.

Enhanced GDM Algorithms for College Mathematics Teaching Quality Evaluation Under Interval-Valued Intuitionistic Fuzzy Sets

The college mathematics teaching quality evaluation is the multiple-attribute group decision-making (MAGDM). Currently, the Exponential TODIM (ExpTODIM) and MABAC was executed to put forward MAGDM. The interval-valued intuitionistic fuzzy sets (IVIFSs) are executed for portraying fuzzy data during the college mathematics teaching quality evaluation. In this study, the interval-valued intuitionistic fuzzy number ExpTODIM-MABAC (IVIFN-ExpTODIM-MABAC) approach is put forward the MAGDM with IVIFSs. At last, numerical example for college mathematics teaching quality evaluation is executed to verify the IVIFN-ExpTODIM-MABAC. The major contributions are executed: (1) the ExpTODIM-MABAC based was extended to IVIFSs along with Entropy model; (2) the entropy is employed to execute the weight under IVIFSs. (3) the IVIFN-ExpTODIM-MABAC approach is put forward MAGDM with IVIFSs; (4) numerical example for college mathematics teaching quality evaluation and comparative analysis is executed to proof the IVIFN-ExpTODIM-MABAC approach.

Nursing students’ evaluation of clinical placement education quality: A national database analysis

AimTo report nursing student ratings of clinical placement education quality. BackgroundAustralian nursing students must complete specified clinical placement hours which must be monitored and evaluated. DesignA quality improvement evaluation design, incorporating survey. MethodsParticipating universities used QR codes and weblinks to distribute a survey between January and December 2023. The validated Placement Evaluation Tool (PET – Nursing) incorporates 20 items; Clinical Environment (11 items), Cronbach’s alpha =.94 and Learning Support (8 items), Cronbach’s alpha =.96 and one item rating satisfaction. ResultsNursing students from 36 universities submitted 17,705 evaluations. The PET – Nursing mean quality rating was 82.6/95 and a mean satisfaction with clinical placement rating (item 20) was 8.3/10; indicating perceived quality of education was high. Students over 41 years reported higher satisfaction compared to younger students as did male students. International students and those who did not speak English at home were more satisfied than domestic students and those who spoke English. First year students rated placements higher than other years. Placements in emergency and intensive care departments received significantly higher ratings than other placements, with aged care settings rated the lowest. ConclusionThis article reports a benchmark of the educational quality of nursing student placement learning in Australia. The results could be relevant to others seeking to improve the quality of students’ clinical learning. Stakeholders need to leverage the reported strengths that enhance student experiences and address the issues and concerns raised to improve the educational quality of nursing students’ clinical learning experiences.

ENHANCING COMPETENCIES OF FUTURE ELEMENTARY EDUCATION TEACHERS IN QUALITY ASSESSMENT THROUGH INTERDISCIPLINARY INTEGRATION

This article emphasises the significance of interdisciplinary integration in enhancing the competencies of future primary education teachers for comprehensive evaluation of education quality, thereby expanding their capabilities. It outlines methods to help teachers better understand the complex factors influencing educational outcomes.

Research and Consideration on the Reform Path of Practical Teaching Quality Evaluation in the Five-Year System of Higher Vocational Colleges

Practice teaching is an important part of the five-year system of higher vocational personnel training. A perfect practice teaching quality evaluation system is an important measure to test the effect of talent training and promote the continuous improvement of teaching quality. Based on this, this paper studies the reform path of practical teaching quality evaluation in higher vocational colleges for five years. Firstly, it expounds on the significance of the reform of practical teaching quality evaluation, then analyzes the existing problems in the current practical teaching quality evaluation, and puts forward the corresponding reform path given the existing problems. Including scientific formulation of evaluation standards, focus on practical teaching process, establishment of daily evaluation mechanism, construction of five-year continuous training and improvement mechanism, and optimization of teacher team construction, to improve the quality of practical teaching in five-year vocational colleges and cultivate more high-quality and high-skill applied talents for the society.

The application effect of the segmented teaching method in training medical students on clinical practice skills

BackgroundThe surgical clinical practice skill training is an important part of medical undergraduate education. Surgical skills are complex and difficult to master. However, the traditional teaching method has some disadvantages, for example, low student participation, weak learning atmosphere, inadequate mastery of the subject matter. We innovatively put forward the segmented teaching method in the field of clinical practice skills training. The segmented teaching method refers to dividing a specific teaching content into several relatively independent parts and providing segmented practice for each part. This approach enhances students’ learning outcomes.The aim of this controlled study is to investigate the effects of the segmented teaching methods on clinical practice skills training in medical students.Methods31 medical students participating in clinical practice skill training at The First Affiliated Hospital of University of South China from March to April 2024 were randomly assigned to either the experimental group (n = 16) receiving segmented teaching method or the control group (n = 15) receiving traditional teaching method. After completion of practical exercises, both groups underwent operational assessments, theoretical assessments, Mini-Clinical Evaluation Exercise (Mini-CEX), and Student Evaluation of Educational Quality (SEEQ) for teaching quality evaluation. A comparative analysis of the results between the two groups was conducted.ResultsAfter implementing the program, there were no statistically significant differences (P > 0.05) between the experimental and control groups in theoretical assessment scores, Mini-CEX clinical judgment scores, and SEEQ teaching quality evaluation scores. However, compared to the control group, the experimental group demonstrated better operational assessment scores, higher Mini-CEX scores in history taking, physical examination, professionalism, doctor-patient communication, organizational efficiency, and comprehensive abilities, with statistically significant differences (P < 0.05).ConclusionThe application of segmented teaching method in clinical practice skill training for medical students yields favorable training outcomes.

Construction and Practice of Teaching Evaluation System Based on Data Mining

The teaching quality evaluation system based on data mining technology can accurately and fairly identify the core driving factors to improve teaching quality. This method adopts the analysis of big data correlation rules, including data collection and processing preparation steps, builds the data warehouse of association rules, and then generates an educational quality evaluation framework using the principle of data mining. Based on this, this paper analyzes the construction design and method of the teaching evaluation system under data mining, hoping to provide help for the improvement of the teaching evaluation system and the improvement of teaching quality.

Online and Face-to-Face Education Quality Evaluation in the repercussions of the "Covid-19" pandemic according to the point of view of the faculty of Education members at Kuwait University

This study targets the quality of online and face-to-face education in the repercussions of the (Covid-19) pandemic from the point of view of the faculty of Education members at Kuwait University. The descriptive analytical method was adopted. A total of 90 faculty members of Kuwait University were recruited. The results reveal that the quality of education was higher in face-to-face learning in comparison with online learning. However, no statistically significant difference was found between the online and face-to-face evaluation methods according to the perceptions of the faculty members. The study encapsulates recommendations to increase the number of courses to train the faculty members and enhance their skills related to online education, and to redesign the educational curricula and pedagogical strategies to achieve educational outcomes. The findings of the study are helpful to improvise the quality of online learning and teaching and learning experiences of faculty and students of Kuwait University.

Change and Development of Digital Classroom Teaching Quality Evaluation in Vocational Colleges

To further implement the fundamental task of cultivating morality and cultivating people, and actively promote the reform effect of digital classroom teaching quality evaluation in vocational colleges, educators should establish a more perfect and scientific teaching evaluation mechanism, which is also the premise of further teaching work. At present, much teaching quality evaluation work is usually result-oriented, lack of evaluation of the teaching process, and a lack of clear evaluation criteria for high-quality teaching AIDS, ideas, which will hinder the development of digital classroom teaching quality evaluation work in vocational colleges. Given this, this paper will analyze the digital classroom teaching quality evaluation of vocational colleges and put forward some strategies for your colleagues’ reference only [1].

Research on Evaluation of College-Classroom Teaching Quality Based on Pentapartitioned Neutrosophic Cubic Sets and Machine Vision

University-teaching quality evaluations are crucial for assessing teachers’ effectiveness and enhancing students’ learning in classrooms. To improve the evaluation efficiency, this study suggests a creative classroom evaluation approach by using machine vision and pentapartitioned neutrosophic cubic set (PNCS). First, this study uses machine vision technology to establish a PNCS to capture the students’ states in classrooms. Second, it proposes four entropy functions to determine the attribute weights. Third, it combines the improved entropy weight functions with the PNCS to evaluate the teaching effectiveness. This study’s practical price is to introduce big data theories into teaching evaluation fields. Last, an example is provided to confirm the efficacy and applicability of the evaluation approach suggested in this study.

Enhanced Cross-Entropy Exponential TODIM Framework for Interval-Valued Pythagorean Fuzzy Information and Applications to Art Teaching Quality Evaluation

Art teachers in preschool education need to possess not only high professional competence but also a commitment to continuous learning to enhance their comprehensive teaching abilities. The art teaching quality evaluation in preschool education programs at vocational colleges is multiple-attribute group decision-making (MAGDM). Currently, the Exponential TODIM and cross-entropy approach was employed to address MAGDM. Interval-valued Pythagorean fuzzy sets (IVPFSs) serve as a strategy for characterizing uncertain data during the art teaching quality evaluation in preschool education programs at vocational colleges. In this study, the interval-valued Pythagorean fuzzy number cross-entropy Exponential TODIM (IVPFN-CE-ExpTODIM) approach is developed to bring up MAGDM problems under IVPFSs. To validate the proposed method, a numerical study is conducted on the art teaching quality evaluation in preschool education programs at vocational colleges.

Deep learning perspective on the construction of SPOC teaching model of music and dance in colleges and universities

In the era of knowledge economy, social development has higher requirements for artistic talents’ quality. The teaching mode of music and dance in colleges and universities needs to be changed urgently. This study introduced deep learning theory and designed a SPOC teaching mode for music and dance in universities to improve the quality of music and dance teaching. Firstly, the K-means clustering algorithm was used to extract the features of online learning behavior. Radial basis function neural network was used to predict students’ performance to improve teachers’ mastery of students’ online learning behavior. Subsequently, the teaching quality evaluation system was constructed using hierarchical analysis. Finally, the effectiveness of the teaching model was tested. The results showed that under this teaching model, students’ overall literacy score reached a maximum of 11.5, and their average score in music and dance reached a maximum of 94, an increase of 11 points compared to the SPOC teaching mode. This indicates that the teaching mode gives full play to the advantages of SPOC teaching, enhances students’ enthusiasm and initiative in learning, and improves their professionalism and comprehensive quality.

Comparative analysis of research trends in teaching quality evaluation: A visual exploration using CiteSpace knowledge mapping in the context of the COVID-19 pandemic

Comparative analysis of research trends in teaching quality evaluation: A visual exploration using CiteSpace knowledge mapping in the context of the COVID-19 pandemic

The Application of Analytic Hierarchy Process Method in the Evaluation of Educational Quality in Colleges and Universities

Talent quality is the lifeline of colleges and universities. Based on employment guidance, this paper establishes a student quality evaluation and control system including knowledge, moral character, and ability, and uses the Analytic Hierarchy Process (AHP) method to analyze the factors affecting the quality of education in colleges and universities. In addition, some suggestions are provided to improve the quality of students.

Application of Video Abnormal Behavior Detection Algorithm in Evaluation of Track and Field Teaching and Training Effect

With the development of track and field, people pay more and more attention to the quality of classroom teaching of track and field technology, and the evaluation of teaching quality plays a key role in it. In today's educational reform, teaching evaluation plays an important role as an important method to test teachers' teaching and students' learning. With the rapid development of machine learning, especially deep learning, image-based individual abnormal behavior detection technology is becoming more and more mature, but there are still many difficulties to be solved in video-based group abnormal behavior detection technology. Therefore, it is necessary to study the detection algorithm. Based on machine vision theory, image processing theory and video analysis technology, this paper studies three key technologies involved in human abnormal behavior detection in video: moving target detection, moving target tracking and abnormal behavior detection.

The analysis of teaching quality evaluation for the college sports dance by convolutional neural network model and deep learning

This study aims to comprehensively analyze and evaluate the quality of college physical dance education using Convolutional Neural Network (CNN) models and deep learning methods. The study introduces a teaching quality evaluation (TQE) model based on one-dimensional CNN, addressing issues such as subjectivity and inconsistent evaluation criteria in traditional assessment methods. By constructing a comprehensive TQE system comprising 24 evaluation indicators, this study innovatively applies deep learning technology to quantitatively assess the quality of physical dance education. This TQE model processes one-dimensional evaluation data by extracting local features through convolutional layers, reducing dimensions via pooling layers, and feeding feature vectors into a classifier through fully connected layers to achieve an overall assessment of teaching quality. Experimental results demonstrate that after 150 iterations of training and validation on the TQE model, convergence is achieved, with mean squared error (MSE) decreasing to 0.0015 and 0.0216 on the training and validation sets, respectively. Comparatively, the TQE model exhibits significantly lower MSE on the training, validation, and test sets compared to the Back-Propagation Neural Network, accompanied by a higher R2 value, indicating superior accuracy and performance in data fitting. Further analysis on robustness, parameter sensitivity, multi-scenario adaptability, and long-term learning capabilities reveals the TQE model's strong resilience and stability in managing noisy data, varying parameter configurations, diverse teaching contexts, and extended time-series data. In practical applications, the TQE model is implemented in physical dance courses at X College to evaluate teaching quality and guide improvement strategies for instructors, resulting in notable enhancements in teaching quality and student satisfaction. In conclusion, this study offers a comprehensive evaluation of university physical dance education quality through a multidimensional assessment system and the application of the 1D-CNN model. It introduces a novel and effective approach to assessing teaching quality, providing a scientific foundation and practical guidance for future educational advancements.