Education Quality Indicators Research Articles

Economic freedom and the quality of education

AbstractThis paper finds robust evidence that economic freedom improves the quality of education. This is probably mainly because economic freedom incentivizes parents to invest in high‐quality education for their children and helps them to do so. It also incentivizes and helps both governments and private providers to deliver high‐quality education. The paper uses two different indicators of educational quality: PISA scores and the World Bank's harmonized test scores. The magnitudes of the estimated effects of economic freedom on both indicators are substantial. They are even larger once the indirect impact of economic freedom via GDP per capita and, to a lesser extent, once the indirect impact via government education expenditure is taken into account. The paper uses data on up to 49 countries for PISA scores and up to 137 countries for World Bank scores. It accounts for the endogeneity of economic freedom and controls for all major determinants of educational quality.

Associations of schooling type, qualification type and subsequent health in mid-adulthood: evidence from the 1970 British Cohort Study

BackgroundEducation is thought to benefit health. However, existing studies have predominantly focused on educational attainment—the type of institution attended has been overlooked, despite being an important indicator of education resources,...

Analysis of factors influencing medical students’ learning engagement and its implications for teaching work—— a network analysis perspective

PurposeHigher medical education has always been a major project in the fields of education and health, and therefore, the quality of education has received much attention. Learning engagement has emerged as a significant indicator of teaching quality, attracting considerable research attention. This study aims to explore the relationship between medical students’ learning engagement and their sense of school belonging, professional identity, and academic self-efficacy.MethodsWe conducted an online survey using convenience sampling method with 311 medical students. We employed Revised version of the Utrech Work Engagement Scale-Student (UWES-S), Chinese version of the Psychological Sense of School Membership (PSSM) scale, Academic Self-Efficacy Scale, and the questionnaire of college students’ speciality identity for evaluation. Network analysis was used to analyze the relationships among these factors.ResultsMedical students’ overall performance in school showed a positive trend. However, there is still room for improvement. In the network structure of learning engagement and its influencing factors, the “emotional” aspect of professional identity (EI = 1.11) was considered to be an important node with strong centrality. And “academic competence self-efficacy” aspect of academic self-efficacy (BEI = 0.72) was considered an important node with strong transitivity.ConclusionDeepening medical students’ emotional identification with their profession and enhancing their confidence in their academic abilities may improve their learning engagement and educational quality.

Quality indicators in teacher education

Quality indicators in teacher education

Teaching Quality: An Unexamined Element of Special Education Teacher Turnover

Little is known about the quality of the special educators who move schools, switch to general education, or leave teaching. In this study, the author examined if turnover (moving schools within a district, moving schools between districts, switching to general education, or leaving teaching in the state) was associated with two common indicators of teacher quality: value-added scores or teaching observation scores. On average, special educators’ probability of leaving teaching in the state declined as their value-added score increased, after accounting for the characteristics of teachers, their students, and their schools. Observation scores were similarly negatively associated with leaving and with moving within or between districts. Eight percent of special educators switched to general education positions, and the probability of switching was not associated with teachers’ value-added or observation scores. The author discusses the implications for ensuring schools retain effective special educators while noting the limitations of current measures of special educator quality used in practice.

Development of the Clinical Placement Quality Survey – Educator (CPQS-E) Tool to Evaluate the Quality of Physiotherapy Clinical Placements

Background: Increasing demand for entry-level clinical education placements has resulted in changes to traditional models. In this evolving landscape, the ability to effectively assess clinical placement quality is critical. However, existing tools are not specific to physiotherapy and/or have focused on student’s perspectives. Purpose: To design a tool that can be utilised by clinical education providers to measure the quality of physiotherapy clinical placements. Methods: A survey was developed based on published recommendations for quality indicators in clinical education. Content and face validity were established using an expert panel of clinical educators (n=18). Test-retest reliability was tested via physiotherapy clinical educators (n=62) completing the survey twice over a two-week period. Reliability of the survey was assessed using intraclass correlation coefficients (ICC), test-retest percentage agreement, and Cronbach’s alpha. Results: The ICC of 0.87 indicated minimal measurement error. The majority (98%, n=62) of test items met criteria for close agreement. The correlation coefficient of reliability ranged from 0.73 to 0.87 across four defined constructs. Conclusion: Initial assessment of the Clinical Placement Quality Survey - Educator (CPQS-E) tool indicates that its properties provide a valid and reliable measure of entry-level physiotherapy placement quality from the perspective of the clinical educator.

Data Analysis of Student Academic Performance and Prediction of Student Academic Performance Based on Machine Learning Algorithms

With the development and popularization of education, the quality of education has become one of the key factors in the development of a country. And students' academic performance, as one of the important indicators of education quality, has been attracting much attention. This paper mines and analyzes the data affecting students' academic performance, and also conducts a predictive study of students' academic performance using logistic regression model. In this study, 30 indicators such as gender, age, family size, parental education, parental occupation, family relationship, health, and the number of drinks per this paperek and per month this paperre used as input variables, and students' academic performance was categorized into SUCCESS and FAIL, and the training and test sets this paperre divided according to the ratio of 7:3, and the logistic regression model was used for training and prediction. The results show that the logistic regression model has high prediction accuracy in predicting students' academic performance (whether they fail or not), with an accuracy of 95.8%, precision of 96.7%, recall of 95.1%, and F1 of 95.8%. This indicates that the logistic regression model has high accuracy and reliability in predicting students' academic performance. The results of this study are important for schools and educational organizations. Through the prediction of students' academic performance, schools can identify students' learning problems in time and take targeted measures to help students improve their academic performance. Meanwhile, this study also provides some useful reference information for individual students to help them better understand their learning situation, adjust their learning strategies in time and improve their learning efficiency. In the future, the method can be further explored and improved to enhance the accuracy and reliability of the prediction and to provide better support and assistance for students' learning and development.

THE IMPORTANCE OF QUALITY IN EDUCATION

This paper presents as a general objective the relationship between quality and its indicators, presenting the main challenges and strategies to promote quality in education, highlighting the importance of a holistic approach that takes into account not only the pedagogical aspects, but also the socio-emotional ones, cultural and technological. From this perspective, the different elements that contribute to the construction of quality education and the measures that can be adopted by educational institutions to achieve this desired objective will be discussed. Present the need to use quality indicators in education and teaching-learning environments by analyzing the benefits that these tools can bring to society, and highlighting their importance for 21st century education. The transformations caused by quality education are essential for the human, social, economic and democratic development of a society. Investing in improving education is investing in the future of a nation and its future generations. students, there is still a need to establish pedagogical access limits. If there is the possibility of access and a quality pedagogical proposal, the student becomes a professional and a competent citizen, with the skills required in this century and capable of applying the effective learning acquired.

A Parameter Assessment of Teaching Quality Indicators Based on Data Class Mining Fuzzy K-Mean Type Clustering

This paper proposes a data-based mining and hesitant fuzzy C-canopy-K mean clustering degree algorithm and uses it in the parameter assessment model of teaching quality indicators. Simulation and training are carried out through data class mining, and information input, followed by combining the hesitant fuzzy K-mean classification assessment method, which involves a hesitant fuzzy type evaluation system, a neural network identification and prediction system, and an application system for module identity verification. The simulation results show that the results of the six simulation conditions are consistent with the actual results, with only slight differences in some amplitudes, and a high degree of consistency in the overall trend, the change rule, and the average peak value. Through the prediction model processing in this paper, the teaching quality index parameter assessment has high accuracy and can reach more than 95.0%, in addition, the development of the law also fits very well. a, b, c, d four kinds of teaching quality parameter assessment of the average calculation of the assessment speed increased by 52.5%. In addition, the assessment test after the integrated design of the module shows that the system can effectively identify the four clustering identification processes that can be seen as excellent, good, medium, and poor; at the same time, the test data show that the system class effectively for teaching quality indicator parameter assessment.

Inclusive Education in South Korea

Over the past few decades, inclusive education in South Korea has continued to grow both in quantity and quality. The purpose of this article is twofold: (a) to report on the legal basis and the current status of inclusive education in South Korea and (b) to synthesize policy tasks and prominent outcomes related to inclusive education in South Korea. The major findings are as follows. First, according to the 2022 Special Education Annual Report provided by the Ministry of Education, approximately 73% of students eligible for special education received either part-time (56% of students) or full-time (17% of students) inclusive education. Second, it was found that there were significant outcomes in the five elements of support (i.e., human support, social climate support, physical environment support, curriculum support, and financial and operational support), which are quality indicators of inclusive education. Based on these findings, we discuss issues of inclusive education, future directions, and suggestions for the further development of inclusive education in South Korea.

The Quality of Education in 50 Countries Reviewed from Sustainable Development Goals: Systematic Literature Review

Education is an essential aspect of a country. This research aimed to look at countries that implement good quality education and find out what the indicators of the country are in improving the quality of education for sustainable development or see which indicators are used the most in quality education. This research is a systematic literature review. Based on the PRISMA method that has been carried out, a total of 51 journal articles were used in the literature study, and they were obtained from Google Scholar, DOAJ, ScienceDirect, and PubMed. The research results show that indicators of quality education are measured by reliable teaching staff, lifelong education, and completeness of facilities and infrastructure. Of the 51 journal articles examined, 20 journal articles used the indicator of reliable teaching staff as an indicator of education quality, 17 journal articles used lifelong education as an indicator of education quality, and 22 journal articles used indicators of completeness of facilities and infrastructure. These results make completeness of facilities and infrastructure the key to success in creating quality education for sustainable development goals.

Evaluating education quality as a research instrument: A systematic review

The pursuit of quality reflects a fundamental aspiration toward perfection, embodying a commitment to ideal principles and standards. Those who strive for excellence are expected to imbue their work with a sense of conscience and morality. This is particularly salient in organizations that provide services to individuals, including universities, schools, companies, and other educational institutions. In educational contexts, the presence of conscience and morality is crucial for several reasons. First, these attributes cultivate a favorable and principled atmosphere that encourages sincerity, uprightness, and impartiality among students, teachers, and staff members. The aim of this study was to investigate the concept of quality in education and the assessment methods used, drawing on previous studies. Despite numerous studies on this topic, a comprehensive understanding of the quality of education and evaluation tools has yet to be achieved. This study emphasizes the importance of educational quality and stresses the need for educational institutions to gain a thorough understanding of it and stay up-to-date with the latest developments in evaluation methods. Quality in education pertains to the extent of progress made and the fulfillment of expectations by students, parents, and teachers. The evaluation of educational quality is crucial, and there are various methods available for this purpose. One method for evaluating educational quality is to analyze students' exam results and compare them to previous results. Additional indicators of educational quality include students' discipline, their ability to participate in higher education, and their employability. Other factors to consider when evaluating educational quality include educational inspection, retention rates in schools, examination type, course quality, efficiency, effectiveness, cost-effectiveness, school management, and guardians' satisfaction with their children's education. By evaluating these aspects, educational institutions can assess the quality of the educational process and implement necessary improvements.

Cross-entropy method for interval-valued neutrosophic number multiple attribute decision making for education quality management evaluation in higher education institutions

Under the premise of today’s socialist modernization construction, the development and progress of the country require more outstanding talents such as aspiring youth and intellectuals to participate, which puts forward higher requirements for education quality indicators and various aspects of operation. As the main institution and environment for implementing educational activities, the effectiveness of school management organization has a direct impact and even a decisive role on the quality of education. Therefore, how to improve the quality management of school education has become a hot topic in the education industry. The education quality management evaluation in higher education institutions is viewed as the multiple-attribute decision-making (MADM) issue. In this paper, the interval-valued neutrosophic number cross-entropy (IVNN-CE) technique is built under interval-valued neutrosophic sets (IVNSs) based on the traditional cross-entropy technique. Then, combine traditional cross-entropy technique with IVNSs, the IVNN-CE technique is constructed for MADM under IVNSs. Finally, the numerical example for education quality management evaluation in higher education institutions was constructed and some comparisons is employed to verify advantages of IVNN-CE technique. The main contribution of this paper is constructed: (1) the cross-entropy model is extended to IVNSs; (1) the CRITIC technique is employed to construct the attribute weights under IVNSs; (3) the IVNN-CE technique is constructed to manage the MADM under IVNSs; (4) a case study about education quality management evaluation in higher education institutions is constructed to show the built technique; (5) some comparative algorithms are constructed to verify the rationality of IVNN-CE technique.

Quality culture, university-industry collaboration, and perceived employability among vocational students in China: a Yanpei Huang perspective.

Students' perceived employability (SPE) can be seen as one of the indicators of technical and vocational education and training (TVET) quality. However, less is known about the determining factors of SPE in vocational education. As the founder of modern vocational education in China, Yanpei Huang has written a large volume on ensuring students' employability and the quality culture of TVET. Nowadays, as the feature and nature of TVET, university-industry collaboration (UIC) has been promoted worldwide. The primary objective of this study was to investigate the influence of quality culture from Yanpei Huang's perspective (YHQC) on the SPE and the UIC role in the relationship between YHQC and SPE in a TVET university in China. Data were collected by questionnaire from 341 students from one vocational education university in China. The questionnaire included measures of quality culture, perceived employability, and UIC. The Structural Equation Modelling by AMOS 25 was used to test the proposed hypothesis. The results indicate that YHQC acts as a significant factor in enhancing SPE, and UIC is found to act as a partial mediator in this relationship. This study has contributed to the literature and practices by presenting a comprehensive quality culture from Yanpei Huang's perspective, confirming the above relationship, and providing practical suggestions for stakeholders to develop a quality culture in TVET institutes, promote UIC, and enhance SPE.

Качественные характеристики школьного образования как показатель политико-географического положения стран

The correlations between the qualitative characteristics of school education and the human development index and its components, according to UN data, are examined using sets of countries. They take into account educational characteristics, indicators of schoolchildren’s performance, identified in various countries by the international programs TIMSS, PISA, PIRLS and the number of gold medals at international olympiads in various academic disciplines. Components of human development – life expectancy, gross national income, average and expected years of schooling. Positive correlations, in most cases significant, between the phenomena under consideration have been established. The distribution of educational indicators taken into account by region of the world is considered. Using the world-system analysis, it was found that there is no complete correlation between the country's place in the international system and the level of schoolchildren's academic performance and medalists in school discipline Olympiads. It is noted that the Russian Federation and many countries geographically close to it are characterized by a gap between the quality indicators of school education and the level of development. It is suggested that the quality of school education is a strong and insufficiently implemented prerequisite for the development of the Russian Federation.

University Student Satisfaction: Online Text Review of Private University in Surabaya

In the contemporary educational landscape, online platforms have become crucial in assessing student satisfaction, which is an essential indicator of educational quality. This study investigates student satisfaction at private universities in Surabaya, Indonesia, through the lens of online text reviews. Utilizing a dataset of 1548 reviews, this research employs a co-occurrence network analysis to identify key factors influencing student perceptions. Our findings reveal that aspects such as campus facilities, quality of education, and economic considerations significantly impact satisfaction levels. The implications of these insights are substantial for institutional strategies aimed at improving student experience and enhancing educational outcomes. The study contributes to the understanding of student satisfaction in a digital era, highlighting the role of online reviews in shaping educational improvement efforts.

Ensuring sustainable education through the management of higher education quality indicators

Ensuring sustainable education through the management of higher education quality indicators

Project development with STEM features

This article presents an analysis of selected projects developed at the Tecnológico Nacional de México Salvatierra (TecNM-ITESS). These projects help students to develop STEAM skills. Mechatronics and TIC’s engineering programs are included in our case of study. The first part of this article, the ITESS operational framework is presented. Then, it is described Bloom's taxonomy and the PISA tests as reference tools for the development and measurement of student’s capabilities. Also, education quality indicators are presented for the TecNM-ITESS and state government of Guanajuato. Indicator and STEM skills are studied to find relationships. In addition, different academic events and calls for projects that facilitate the participation of students in activities that promote STEAM skills are discussed. In a second part, some projects where students have participated are presented, the strategies used for the dissemination, identification and training of students are discussed. As well as, a sentiment analysis is presented where data has been collected from students who were involved in projects.

Higher Education Quality Indicators: A Scale Development Study

The purpose of this research is to develop a Likert-type scale aimed at determining how quality indicators in higher education are perceived by faculty members. A pilot study of the research was conducted with the participation of 390 faculty members. As a result of the factor analysis applied to test the construct validity of the 67-item draft scale, a measurement tool consisting of 9 dimensions and 49 items was developed. The first dimension is named Education and Instruction, the second is Structure of the University, the third is Socio-Cultural Opportunities, the fourth is Internationalization, the fifth is Economic Opportunities, the sixth is Student Requirements, the seventh is Accreditation, the eighth is Preferability, and the ninth is Technological Competence. The overall Cronbach's Alpha reliability coefficient of the scale has been calculated as 0.96. Additionally, as a result of the independent groups t-test for the reliability of the scale, it has been determined that items and factors are distinctive between the lower and upper 27% groups; the item-total and item-remainder correlation values are significant. Correlation coefficients between factors and the test-retest correlation coefficient for the entire scale have been found significant. Based on the conducted analyses, the validity and reliability of the scale have been established. The scale has been named the Higher Education Quality Indicators: Faculty Member Scale (HEQIFMS).

Surviving and thriving: How changes in teaching modalities influenced student satisfaction before, during and after COVID-19

This paper leverages analytics methods to investigate the impact of changes in teaching modalities shaped by the COVID-19 pandemic on undergraduate students’ satisfaction within a Spanish brick-and-mortar higher education institution. Unlike research that has focused on faculty- or programme-level data, this study offers a comprehensive institutional perspective by analysing large-scale data (N = 83,532) gathered from satisfaction surveys across all undergraduate courses in eight faculties from 2018 to 2021. The longitudinal analysis revealed significant changes (p < 0.05) in satisfaction indicators, particularly overall satisfaction and perceived workload. During the emergency remote teaching period, there was a significant decrease in satisfaction and high levels of variability across courses. However, a year after emergency remote teaching, with increased implementations of technology-supported online and mixed teaching modalities, satisfaction measures not only recovered but exceeded pre-COVID levels in the aforementioned indicators when the teaching modality was fully co-located. The variability of answers also reached historical lows, reflecting more uniform student experiences. These findings highlight the resilience of educators and the current higher education system and suggest a capacity to learn and improve from disruptive pedagogical changes. The study also provides insights into how data analytics can help monitor and inform the evolution of teaching practices. Implications for practice or policy Higher education institution administrators should improve the understanding of the effects derived from changes in their teaching and learning models, for example, in teaching modalities and related technology support. Student satisfaction data analytics offer useful indicators to study the impact of those effects. Higher education institutions should provide support for educators to ensure minimal deviations from expected averages of educational quality indicators regardless of the educators’ capacity to adapt to changes in the teaching models.