Teaching Quality Assessment Research Articles

Retracted: Higher Education Environment Monitoring and Quality Assessment Model Using Big Data Analysis and Deep Learning.

[This retracts the article DOI: 10.1155/2022/7281278.].

Fuzzy comprehensive evaluation model in the evaluation of English teaching quality

Evaluating English teaching quality is vital for improving knowledge-based developments through communication for different aged students. Teaching quality assessment relies on the teachers’ and students’ features for constructive progression. With the development of computational intelligence, optimization and machine learning techniques are widely adapted for teaching quality assessment. In this article, a Quality-centric Assessment Model aided by Fuzzy Optimization (QAM-FO) is designed. This optimization approach validates the student-teacher features for a balanced model assessment. The distinguishable features for improving students’ oral and verbal communication from different teaching levels (basic, intermediate, and proficient) are extracted. The extracted features are the crisp input for the fuzzy optimization such that the recurring fuzzification detains the least fit feature. Such features are replaced by the level-based teaching and performance feature that differs from the previous fuzzy input. This replacement is pursued until a maximum recommendable feature (performance/ learning) is identified. The identified feature is applicable for different teaching levels for improving the quality assessment. Therefore, the proposed optimization approach provides different feasible recommendations for teaching improvements.

Education on quality assurance and assessment in teaching quality of high school instructors

Research on language teaching quality has certainly stood out enough to be noticed as the momentum higher school teaching change proceeds to extend and develop. The way to further developing language teaching quality is to further develop teaching quality, and educator assessment is a significant instrument for doing as such. Accordingly, school administration necessitates the turn of events and refinement of a framework for assessing language teaching quality. Thus, hybrid learning technique for assessing the teaching quality of high school instructors should be created. We present an interesting model for assessing the quality of homeroom teaching involving artificial intelligence innovation in high schools, which depends on better hereditary calculations and neural networks. The fundamental thought is to utilize higher request factual elements (skewness, change, second and kurtosis), even vulnerability, Improved Independent Component Analysis (IICA), Holo-entropy based highlights to remove the underlying loads and limits of gathered data. The teaching quality assessment results were enhanced by further developing the neural network’s forecast accuracy and intermingling speed, bringing about a more down to earth plot for assessing high school language teaching quality. We have led simulation investigations and comparative analysis utilizing the Bi-directional Long Short Term Memory (Bi-LSTM) and Convolutional Neural Network (ConvNet/CNN) models. Then, an education quality assessment framework is laid out by hybrid optimizing model parameters which is Seagull Optimization Algorithm (SOA) and Red Colobuses Monkey (RCM).

A Hybrid Education Quality Assessment Method based on Heuristic Optimization Algorithm

Hybrid education is the most effective process of education, which is the mixture of two education processes that help increase the student’s understanding level. In the study, it has been discussed that the intelligent learning environment influences the education style, which allows the students and the educator to understand the topic correctly. Also, from the study, a good bond between the teacher and the students increases the achievement rate in an education system. Therefore, the professional life of the students is also more developed. The study aims to consider the disadvantages of the modern or hybrid education system, and the communication gap is one of the significant disadvantages of education.

Establishing a model of the factors affecting the quality of educational services: A case study of Hanoi University of Mining and Geology

The study built a model of factors affecting educational service quality based on the assessment of student satisfaction. The theoretical model is drawn from domestic and foreign authors and has been adjusted to suit the research context. The results are collected from 886 surveys with full-time students from the faculties of Hanoi University of Mining and Geology, which showed that the quality of educational services of Hanoi University of Mining and Geology is derived by the factors such as (1) Quality of Lecturer, (2) Quality of staff, (3) Support services, (4) Training program, (5) Facilities. The results of the paper also show that there is a difference between students of other faculties, but there aren’t differences in the genders, courses, and performances in the assessment of educational service quality. From these results, the study has proposed recommendations to improve the quality of educational services at this University in order to: satisfy student satisfaction, improve the image of the University, collect attract learners in the recruitment process.

Similarities and differences between CLASS and ECERS-R estimates of educational environment quality.

The conducted research was devoted to comparison of kindergartens' educational environment quality evaluation via ECERS-R and CLASS methods. Both methods were applied in the same kindergarten groups. Therefore, in this study we attempted to find out if the educational environment quality assessments acquired via the two methods mentioned above would coincide. We analyzed the results from the cultural-historical psychology perspective. The educational environment quality assessment has been conducted in 83 Moscow kindergarten groups where study 5 to7 years old preschoolers. The correlation analysis results show that the ECERS-R method subscales are not related to the "Emotional support" CLASS domain, however, a significant correlation with the total ECERS-R score has been revealed. The "Classroom Organization" CLASS domain has the highest number of correlations to the ECERS-R subscales (4) as well as to the total ECERS-R score. The "Instructional Support" domain is connected only to the Parents and Staff subscale within the ECERS-R method. As a result of comparing groups with relatively low and high quality of the educational environment, that were identified based on the evaluation via the ECERS-R and CLASS methods, a good agreement between the results has been revealed. However, a fairly large number of groups with high CLASS scores have made it to the pool of average-low ECERS-R scores, which demonstrates a non-linear connection between the educational environment quality evaluations according to these two methods. Research allows to conclude that the ECERS-R and CLASS approaches complement each other well.

Retracted: Quality Assessment of Physical Education Teaching in Colleges and Universities Based on Joint Neural Network

Retracted: Quality Assessment of Physical Education Teaching in Colleges and Universities Based on Joint Neural Network

Integrated MAGDM framework based on spherical fuzzy sets for teaching quality evaluation of ideological and political courses in universities

With the rapid development of society, ideological and political education courses have occupied a very important position in various courses in major universities, playing a series of important functions and roles in student quality education, excellent quality cultivation, and other aspects. In the new era, the evaluation and assessment of ideological and political education quality is not only the primary factor to improve the teaching quality of ideological and political education courses in universities, but also an important means to promote the deepening reform of ideological and political education. However, there are many problems in the process of evaluating the quality of ideological and political education in colleges and universities at present, such as the deviation in understanding the importance of evaluation, the relatively single evaluation method, and the low quality of application of evaluation results. The teaching quality evaluation of ideological and political courses in universities is a classical multiple attribute group decision making (MAGDM). Spherical fuzzy sets (SFSs) provide more free space for decision makers (DMs) to express preference information during the teaching quality evaluation of ideological and political courses in universities. Therefore, this paper we first extend partitioned Maclaurin symmetric mean (PMSM) operator and IOWA operator to SFSs and develop induced spherical fuzzy weighted PMSM (I-SFWPMSM) operator. Subsequently, a new MAGDM method is established based on I-SFWPMSM operator and SFNWG operator under SFSs. Finally, a numerical example for teaching quality evaluation of ideological and political courses in universities is used to illustrate the proposed method.

Are Classical Assessments Offering Adequate Insight into Post-Pandemic Teaching Methods?

Educators must continuously assess and adjust to maximize the amount of information students retain. One way to evaluate teaching effectiveness is thru pre- and post-semester assessments. Factors such as individual willingness to participate can affect the validity of these assessments. Our hypothesis was that students will more actively participate in a group activity compared with written pre- and post-semester assessments. In this study, we evaluated 3 different types of pre- and post-assessments to assess knowledge retention and participation. Participation decreased as the semester progressed resulting in only 31 of 57 students who completed all 6 of the assessments. There was an interaction (P < 0.001) between the type (individual, team, or activity) and time of assessment. The percentage of correct answers increased (P < 0.001) between pre-semester (average 32.92 ± 1.58) and post-semester assessments (average 47.54 ± 1.58). There was a correlation (P = 0.04) between the final course grade and the post-semester individual written assessment. In conclusion, participation throughout the semester is a major issue in assessing teaching quality and knowledge retention and the utilization of group activities does not appear to impact that participation. However, the best assessment for knowledge learned remains the classical written individual assessment.

Investigating university students’ online proctoring acceptance during COVID-19: An extension of the technology acceptance model

To ensure the normal operation of teaching and meet the needs of teaching quality assessment in the COVID-19 situation, universities in various countries have adopted online proctoring for assessment. The epidemic has accelerated the development of online education. Online proctoring, as an integral part of future online teaching, has not yet drawn sufficient attention. To understand students’ experiences and attitudes towards initial online proctoring, an extended technology acceptance model was utilised to examine the motivations and barriers that influence students’ online proctoring acceptance in terms of technology perception, presence and social influence. Structural equation models were used to analyse data from a questionnaire survey of 760 university students. Results revealed that social influence, social presence and perceived usefulness are the significant predictors of online proctoring acceptance. Social influence and social presence have significant positive effects on online proctoring acceptance through perceived usefulness, and social presence has a positive effect on perceived ease of use. However, perceived ease of use has a significant negative effect, while place presence has no significant effect. Implications, limitations and future work are discussed at the end. Implications for practice or policy: Online proctoring organisers can bring a better exam experience to students by ensuring the flexibility and integrity of online proctoring. Online proctoring workers can improve students' exam experience by building a positive group atmosphere in the early stages of online proctoring applications. Social recognition and support for online proctoring can enhance students' choice and willingness to use online proctoring and increase opportunities for online proctoring development.

External assessment of medical education quality: indicative model development considering paradox of skill.

This study proposes an approach to the external evaluation of medical education programs' quality based on a combination of indicators, including international rankings, external stakeholders' input, and independent agencies' assessments. We modify the success equation with a detailed consideration of the skill component and its decomposition into internal and external quality assurance elements along with authority. We carried out a bibliometric analysis regarding the problem of medical education quality assessment in the context of achieving sustainable development goals. We described the calculation model of external quality assessment indicators through the algorithms of independent education quality assurance agencies' activity and rating indicators shown in the modified Mauboussin's equation. The model considers the economic component (the consequence of achievement) of skill, which is expressed in raising funds from external sources to implement educational and scientific activities. The proposed algorithm for assessing the educational program quality can be applied to benchmark educational program components, complete educational programs within the subject area, and the educational institution for different areas. We propose a "financial" model for educational program quality based on the analysis results. The model makes it possible to determine the need for additional focused funding of the educational program based on the individual analysis of the external evaluation criteria of the achievement level. This study analyzes the accreditation results of more than 110 educational programs in 2020 and 8 months of 2021 within the direction 22 "Medicine" (according to the national classification of fields of knowledge) (state and private Ukrainian medical universities).

Cloud education chain and educational quality assessment based on hybrid quantum neural network algorithm

Cloud education chain and educational quality assessment based on hybrid quantum neural network algorithm

Key Technologies of Quality Assessment in Network and Distance Education

Key Technologies of Quality Assessment in Network and Distance Education

Investigating the use of fuzzy logical data for evaluating the teaching quality of college teachers

The level of education in colleges is career and development-focused compared to that from high schools. Quality education relies on the teachers’ qualifications, knowledge, and experience over the years. However, the demand for technical and knowledge-based education is increasing with the world’s demands. Therefore, assessing the knowledge of teaching professionals to meet external demand becomes mandatory. This article introduces an Acceded Data Evaluation Method (ADEM) using Fuzzy Logic (FL) for teaching quality assessment. The proposed method inputs the teachers’ skills and students’ productivity for evaluation. The teachers’ knowledge and updated skills through training and self-learning are the key features for evaluating the independents’ performance. The impact of the above features on the student qualifying ratio and understandability (through examination) are analyzed periodically. Depending on the qualifications and performance, the teachers’ knowledge update is recommended with the new training programs. In this evaluation process, fuzzy logic is implied for balancing and identifying the maximum validation criteria that satisfy the quality requirements. The recommendations using partial and fulfilled quality constraints are identified using the logical truth over the varying assessments. The proposed method is analyzed using the metrics evaluation rate, quality detection, recommendations, evaluation time, and data balancing.

Analysis of transurethral resection of prostate videos on YouTube™: Educational quality assessment.

Our aim was to evaluate the educational value of transurethral resection of prostate (TURP) videos on YouTube. A comprehensive search was conducted for TURP videos on YouTube. Based on the Laparoscopic Surgery Video Educational Guidelines we created a checklist which includes 20 items for evaluation of the videos. IBM SPSS statistics was used for analysis. A total of 104 surgical videos were assessed. The mean view count was 15647.3 (21-324.522, SD 47556.4). Video image quality found as low for 57.7% of videos. Both staff (76%) and resident (75%) rated most of the videos low educational quality. No statistically significant difference was found between staff's total points (mean 4.35 ± SD 2.9) and resident's total points (mean 4.63 ± SD 3.3) (p: 0.761). Positive correlation was found between view count and staff's total points (r: 0.242 p < 0.05), resident's total points (r: 0.340 p < 0.01). There was also positive correlation between number of likes and staff's total points (r: 0.375 p < 0.01) and resident's total points (r: 0.466 p < 0.01). Most TURP surgical videos on YouTube are low quality. Higher educational quality videos with detailed explanation of the procedure are needed on this subject. We believe this study could be a guide for future high quality TURP videos.

Assessment of Physical Education Classroom Teaching Quality: Basis for Enhanced Instructional Delivery

Assessment of Physical Education Classroom Teaching Quality: Basis for Enhanced Instructional Delivery

The Path of Constructing a Platform of Academic Affairs System based on Continuing Education in Universities - Taking Zhejiang Open University as an Example

As a consequence of the field's constant expansion year after year, the path of developing the academic affairs system platform, which is directly linked to college continuing education, has received increasing attention. Using Zhejiang Open University as a starting example, this study discusses the challenges with existing academic affairs administration in colleges and universities. It discovers that the primary concerns are the large workload of class schedule management, the lack of data support for teaching inspection&amp; teaching quality assessment, the redundant construction of multiple systems &amp; multiple entrances, teachers' workload accounting is unclear, student safety issues and student mental health. We handle the difficulties one at a time as we create the platform, by establishing the institutional assurance system, integrating information service entrances and so on. Simultaneously, we focus on recommendations as exploring additional features, evaluating the effectiveness in various educational contexts, and adapting the platform to different institutions. As a consequence, those actions can make contributions such as improved top-level design, data effectiveness and scientific decision-making.

The validity of student ratings of teaching quality: Factorial structure, comparability, and the relation to achievement

Student ratings are widely used to assess teaching quality in primary and secondary education. This necessitates a thorough examination their validity and reliability in such contexts. To this end, we present validity evidence for using student ratings of teaching quality based on their factorial structure, comparability across grades and subjects, and relation to achievement. Based on data from the 2019 Trends in Mathematics and Science Study (TIMSS) and its national extensions in Norway (N = 3951 5th graders and N = 4575 9th graders), we could confirm a theoretically assumed three-dimensional factor structure (i.e., classroom management, cognitive activation, and supportive climate). Moreover, classroom management and supportive climate were more comparable across grades and subjects then cognitive activation. Finally, classroom management was associated with achievement across all groups, whereas other dimensions showed mixed results, especially across grades. Overall, the findings indicate that students, especially in Grade 9, can provide a valid assessment of teaching quality.

Construction of a mathematical modeling teaching quality assessment system for universities based on Eviews model

Abstract Quality assessment of university education and teaching is an essential and important part of teaching and learning activities. Over the years, a large amount of data has been accumulated in teaching and management, but the potential value of these data has not been fully utilized. How to use a large amount of data scientifically, automatically, and more effectively for rational analysis and guidance of current teachers’ teaching work has become a key issue in testing the effectiveness of teaching quality assessment, and an in-depth study is urgently needed. In this paper, we use the Eviews model, regression analysis algorithm, Apriori association rule algorithm, and other techniques. It conducts research on the assessment of teaching quality in Chinese universities. Finally, after completing the construction of the system, the main modules in the system, system management, resource management, quality assessment, and assessment query module, focused on testing. A total of 160 test cases were designed, of which 157 test results met the requirements of the system, and 3 results did not meet the requirements, with a success rate of more than 98%. The results show that the system has no major defects, runs normally, has stable performance, and meets the system requirements for teaching quality assessment in universities.

Lost and Found: University Teachers about the Change of Higher Education Quality

The article considers last three years’ changes of higher education quality from the perspective of university teachers as key actors of an educational process. The study focuses on the main factors infl uencing the quality of higher education and the nature of changes in the post-pandemic educational environment, in particular, through the use of digital solutions. The authors deliver primary (general) results of Russian university teachers’ poll regarding the triggers for changing the quality of higher education, the eff ectiveness of educational and pedagogical activities in the digital environment, as well as points to be paid attention at in ensuring the quality of higher education. The results of the poll show signifi cant changes in higher education over the period studied, especially in applied teaching practices and in lesson formats, these shifts contributing to the change of education quality in general. Global, institutional, and individual infl uencing factors together give multidirectional impact on the quality of education, thus forming diff erent experiences and perceptions of higher education quality dynamics. University teachers, however, are quite diff erently engaged in the university education quality assessment. Due to understanding themselves as key stakeholders in education quality assurance, university teachers identify their course load and additional non-curricular functions as the main barriers in developing their own eff ectiveness. The article is addressed to heads of academic programs and educational institutions, to executive authorities responsible for quality assurance and assessment in higher education, as well as to the representatives of research community in Russian higher education.