Quality Of Higher Education System Research Articles

Factors Influencing the Probability of Dropout in a Romanian Higher Education Institution, Incorporating the Impact of the COVID-19 Pandemic

Dropout rate is an important indicator of the quality of higher education systems, especially in the case of mass education. When the Bologna reform in higher education was introduced, it was hoped that more people would graduate from short-cycle undergraduate courses, but the transition from a more traditional educational model to the Bologna system did not reduce the dropout rates. In Romania, a recent study carried out by UEFISCDI indicates that almost half of the students enrolled in undergraduate programmes in 2015 had not completed their studies by 2021, while Herțeliu et al. (2022) show that 43.8% of students drop out of university while being enrolled in the first year of a bachelor’s degree programme. The current study focuses on two surverys carried out at a Romanian higher education institution (Babeș-Bolyai University), with the aim of identifying individual, socio-demographic and institutional risk factors for university dropout, as well as factors that protect against it. Using factorial analysis, the study reveals that the factors associated with university dropout have a multi-causal character, and are related to both institutional, economic and external factors.

Vastness of Higher Education Development Programme on Enhancing Quality and Sustainable Service Delivery by University Graduates in the Northern Zone Tanzania

Quality, resilience, commitment and sustainable delivery of services has increasingly being a demand for every community in the world. The 21st century has identified the kind of skills that need to be embraced by every individual for one to deliver quality, sustainable and descent work. In response, Tanzania launched the Higher education Development Programme (HEDP) to ensure the attainment of this fundamental objective. This study therefore investigated the vastness of HEDP on enabling quality and sustainable service delivery among university graduates. The study tested two hypotheses. The CIP1P2I evaluation model guide this study. The study employed Convergent design under mixed research approach. The target population for this evaluation study was 18,601 respondents selected from eight (8) Universities in the Northern Zone Tanzania. The target population comprised of 5,118 final year bachelor degree students, 483 lecturers, 8 DVC-academics, 12,292 alumni and 100 employers. The sample was 697 which comprised of 511 final year Bachelor degree students; 48 lecturers; 4 DVC academics; 124 alumni and 10 employers. The sampling techniques included stratified random, purposive sampling techniques and automatic inclusion. Data was collected by using questionnaires, indepth interview guides and document analysis guides. Quantitative data was analyzed by using descriptive statistics where frequencies, percentages, and means were determined. Qualitative data was analyzed through transcription of the texts, generate themes, interpreting, discussion and making conclusions. The study found that, most alumni couldn’t deliver quality and sustainable service as needed by their community. The study concluded that, HEDP has not adequately brought about tangible implications on the quality and sustainability of graduates and thus quality of higher education system is questionable. It was recommended that, universities should reform curriculums that emphasize on acquisition of soft-skills that may enable graduates deliver quality and sustainable services rather than traditional emphasis on academic achievement.

Enhancing student giftedness in open distance e-learning through quality assurance using Donabedian steps

Students must have faith in open distance e-learning institutions' quality assurance methods if they are to have faith in them. The article looks into quality assurance and uses a qualitative approach to grasp the concept. To acquire information, a literature review was used. The discourse and practices about systematic quality assurance in open distance e-learning institutions during the Covid-19 pandemic had institutions panic throughout the world, resulting in market-based models associated with neoliberalism's ideology and policy and expressed in economic rationalities such as new public management, total quality management, public choice, and human capital to a large extent. Quality assurance in open distance e-learning aims to preserve and improve educational quality. In order to evaluate open distance e-learning, quality expectations and criteria must be made clear and public. Quality assurance is critical when it comes to open distance e-learning. The process of analysing, assessing, monitoring, ensuring, maintaining, and improving the quality of higher education systems and programs should be ongoing. As a result, relevant technologies can be utilized as pointers in undertaking quality assurance in open distance e-learning settings by relying on Donabedian processes.

Strategic Leadership as a Mediating Variable between Organisational Climate and Quality Improvement in Higher Education

The quality of higher education systems depends mainly on leaders. This study describes how strategic leadership influences organizational climate and enhances the continuous quality improvement of the university. Besides, this study sought to examine the mediating impact of strategic leadership on the relationship between organizational climate and continuous quality improvement in a specific context of Tanta universities in Egypt. A quantitative research design was used in this study. Data were collected from 165 lecturers from the faculty of medicine. For achieving the study's objective, SPSS version 26 and Smart PLS 3.3 software were used to analyze the data. The study revealed that strategic leadership has a full mediating influence on the relationship between organizational climate and continuous quality management. The study suggests that more emphasis should be laid on organizational climate in terms of university sources. Finally, the study concluded that the organizational climate could be improved through strategic leadership. The study recommended that the top management creates a suitable climate that improves quality improvement in Egypt's public university.

Application of the SERVQUAL Model for the Evaluation of the Service Quality in Moroccan Higher Education: Public Engineering School as a Case Study

The quality of higher education systems currently represents a major challenge for the development of societies. In Morocco, engineering education is at the heart of this development, it is a major and necessary lever which, due to an increasingly demanding job market, faces several challenges. According to Moroccan Directorate for Strategies and Information Systems (2018) these challenges are classified into two categories: quantitative (low rate of Moroccan engineers compared to global figures; 1.57 graduates in engineering per 10,000 inhabitants in 2016) and qualitative (adaptation of the academic curriculum to the needs of the job market). However, little work has been done on the introduction of service assessment tools in higher education in Morocco (Akrim, Figari, Mottier-Lopez, & Talbi, 2010).In our article, we are interested in the SERVQUAL method (SERVice QUALity-Quality of Service). This approach, initially designed to measure customer satisfaction in a company, allows, when applied to higher education, to measure student satisfaction at the university. Based on a bibliographic research, we have identified the five dimensions of the model that impact the quality of service.Through the application of this model to a sample of students from a public engineering school, we have been able to determine that tangible elements and physical installations have the biggest impact on service quality with a negative quality gap (-2.0275). As a result, more efforts are needed in these dimensions to improve service quality.In conclusion, the SERVQUAL model, applied to the educational system and more precisely higher education, allows to quantify the non-quality by measuring the gap between the perception of the students and their expectations for a good service. It has the advantage of helping decision-makers take corrective actions needed to improve the service quality provided by universities as a part of a process of continuous improvement to achieve higher degree of excellence.

Measuring the Service Quality in Higher Education System

Measuring the Service Quality in Higher Education System

Influence of Attitudinal belief on e-learning behavior Among Academics in State Universities of Sri Lanka

The objective of this paper is to investigate the influence of attitudinal belief of “Decomposed Theory of Planned Behavior” (DTPB) on actual e-learning behavior among university academics in Sri Lanka. The study applied a quantitative method by using questionnaire to collect data among university academics. Explorative and Confirmatory Factor analysis was used to examine the reliability and validity. And this study carried out Structural Equation Modeling to assess model fit and through path analysis, the association between variables was investigated. The study resulted that perceived ease of use, perceived usefulness, compatibility, attitude, behavioural intentions and actual behaviour met the indices for model fit. The findings showed perceived usefulness and perceived ease of use associated with attitude while compatibility is not. Attitude significantly and positively associated with behavioural intention. While behavioural intention positively associated with the actual usage this mediates the relationship between attitude and actual behaviour. The e-learning usage of academicians will help to enhance the quality of higher education system in Sri Lanka as well as to magnify the number of university intake as the country seeks to achieve its vision to be “the knowledge hub in the region and a leader in higher education in Asia by 2020”. Though the e-learning adoption studies are growing trend of education and system researchers as evidenced by extant literature, studies on attitude and intention of academicians especially in an emerging economy like Sri Lanka is still lacking. This study attempts to establish the attitudinal factors that contributes actual e-learning behavior of academicians.

The effects of social networks on the flow of international students

AbstractInternational study provides many benefits to the countries that host students, to the students’ home countries and to the students themselves. We extend the empirical knowledge regarding flows of international students, using a panel of data that spans 17 years, 26 host countries and 85 countries of origin. We examine the hypothesis that social networks are an important factor motivating study abroad by including lagged variables of the levels and shares of enrolment in the analysis. The analysis shows that they are significant factors: a 1% rise in a host country's share of an origin country's international student “diaspora” is associated with a 0.09%–0.12% rise in the number of students studying in that host from that origin, 5 years later. This is consistent with the literature on the economics of immigration, which finds social networks to be important, and transitory, in inducing immigration. These effects are found in models that control for other factors as well: earnings differentials, quality of higher education system, distance, common language and colonial relationship. The results suggest that one‐off policies to better recruit or attract international students will have ongoing benefits, in terms of follow‐on recruitment of further students by the initial students.

Pedagogue Performance Assessment (PPA) using Data mining Techniques

Educational Data Mining (EDM) is a developing domain that exploring pedagogical data by applying different machine learning techniques. It can be considered as a research field which provides intrinsic knowledge of teaching and learning process for effective education. The main objective of any educational institution is to provide quality education to their students. One way to achieve highest level of quality in higher education system is by discovering knowledge that predicts pedagogues performance. This paper presents an efficient system model for evaluation and prediction of pedagogue performance in higher institutions of learning using data mining technologies. To achieve the objectives of this work, three classification algorithms like decision tree algorithms(C4.5), support vector machines (SMO) and artificial neural networks (MLP) are chosen to build classifier models on a dataset. The classifier system was tested successfully using case study data from St. Joseph college of Engineering and Technology, Palai. The data consists of the feedbacks that got from the students. The aim of this work is to demonstrate the capability of EDM in illuminating the criteria of fruitful instructor performance as perceived by the students. The result shows the accuracy of classifier models that predicts the performance of pedagogues. Decision tree J48 have higher accuracy of 94.37% than SMO and MLP.

Peru and its new challenge in higher education: Towards a research university.

The paradigm of research universities linked to the emergence of university rankings has unified and universalized the criteria relating to the quality of higher education. This situation has led to multiple responses across global society, which has started rating the quality of higher education systems through these rankings, supported by a series of indicators aligned to the characteristics of research universities. Given that the quality of a country’s higher education is one of the fundamental pillars of its development, many countries have started to take government action in this respect. In the case of Peru this has not taken long, with the approval of Law 30220 in 2014. This aims to regulate the quality of higher education through a series of specific conditions governed by a newly created body known as SUNEDU. This article uses a Delphi panel to analyze the existing relationship between the conditions imposed by SUNEDU and the research universities’ intrinsic characteristics. During the Delphi panel a consensus was reached through an acceptable and stable level of responses, resulting in confirmation that there is alignment between the conditions imposed by SUNEDU and the intrinsic characteristics of research universities.

Fuzzy Association Rule Mining based Model to Predict Students’ Performance

<p class="Abstract">The major intention of higher education institutions is to supply quality education to its students. One approach to get maximum level of quality in higher education system is by discovering knowledge for prediction regarding the internal assessment and end semester examination. The projected work intends to approach this objective by taking the advantage of fuzzy inference technique to classify student scores data according to the level of their performance. In this paper, student’s performance is evaluated using fuzzy association rule mining that describes Prediction of performance of the students at the end of the semester, on the basis of previous database like Attendance, Midsem Marks, Previous semester marks and Previous Academic Records were collected from the student’s previous database, to identify those students which needed individual attention to decrease fail ration and taking suitable action for the next semester examination.</p>

Teachers’ Performance Evaluation in Higher Educational Institution using Data Mining Technique

Educational Data Mining (EDM) is an evolving field exploring pedagogical data by applying different machine learning techniques/tools. It can be considered as interdisciplinary research field which provides intrinsic knowledge of teaching and learning process for effective education. The main objective of any educational institution is to provide quality education to its students. One way to achieve highest level of quality in higher education system is by discovering knowledge that predicts teachers’ performance. This study presents an efficient system model for evaluation and prediction of teachers’ performance in higher institutions of learning using data mining technologies. To achieve the objectives of this work, a two-layered classifier system was designed; it consists of an Artificial Neural Network (ANN) and Decision Tree. The classifier system was tested successfully using case study data from a Nigerian University in the South West of Nigeria. The data consists of academic qualifications for teachers as well as their experiences and grades of students in courses they taught among others. The attribute selected were evaluated using two feature selection methods in order to get a subset of the attributes that would make for a compact and accurate predictive model. The WEKA machine learning tool was used for the mining. The results show that, among the six attributes used, Working Experience, and Rank are rated the best two attributes that contributed mostly to the performance of teachers in this study. Also, considering the time taken to build the models and performance accuracy level, C4.5 decision tree outperformed the other two algorithms (ID3 and MLP) with good performance of 83.5% accuracy level and acceptable kappa statistics of 0.743. It does mean that C4.5 decision tree is best algorithm suitable for predicting teachers’ performance in relation to the other two algorithms in this work. General Terms Data Mining

Assessment of quality of higher education in hostile environment: an analysis on provincialised colleges under Assam University Silchar

Historically low average pass rate has been a perennial challenge for the universities and provincialised colleges in the North-Eastern states of India (Assam, Meghalaya, Mizoram, Nagaland, Tripura, Manipur and Arunachal Pradesh). Pass rate refers to the proportion of students promoted from one semester to the next and also the proportion of students who pass the final examination to be a graduate. The paper attempts to trace the key parameters for quality improvement for higher education in the region and subsequently augment the pass rate. An inductive content analysis was conducted based on focus group interviews at various levels at Assam University, Silchar and its affiliated provincialised colleges. The four broad categories thus identified (academic, administrative, socio-economic and placement issues) were subjected to Pareto 80-20 principle to identify the issues that are to be given priority for evolving the system. The study would help the administrators to measure the quality of higher education system in a hostile environment characterised by adverse topography, political disturbances, skewed distribution of income, widespread poverty and lack of literacy.

Trends in the International Academic Migration: A Case of Spain

Objective : The objective of this paper is to analyses how undergraduate students' mobility has changed after the last economics recession. Research Design & Methods : The study analysed the last data about public and private Universities of higher education system of Spain comparing it at international level in order to find the problems and challenges of the last few years. Findings: The results showed significant imbalances in mobile students' trends by home and host region, especially after a deep restructuration of the higher education system of Spain due to the last crisis. In particular there are substantial differences in tuition fees, scholarships, number of teachers and their skills according to the region and type of university. Consequently international inflows and international study programs and agreements became very important. Implications & Recommendations: A growing number of students who study abroad, especially after the economic collapse of 2008, represents an excellent opportunity for the host countries due to an incomes growth and recruitment opportunities of highly skilled workers. Therefore to adapt the academic offer taking in account the language, needs and diversity of mobile students would increase their number. Also to increase the highly skilled teachers could help to attract these mobile students, and it would improve the quality of higher education system too. Contribution & Value Added: This research provided a value information to understand the current problems, challenges, changes and opportunities of the higher education mobility through the analysis of the case of Spain and international comparisons.

A Study of the Applications of Data Mining Techniques in Higher Education

Data mining is used to extract meaningful information and to develop significant relationships among variables stored in large data set. Few years ago, the information flow in education field was relatively simple and the application of technology was limited. However, as we progress into a more integrated world where technology has become an integral part of the business processes, the process of transfer of information has become more complicated. Today, one of the biggest challenges that educational institutions face is the explosive growth of educational data and to use this data to improve the quality of managerial decisions and student’s performance. The main objective of higher education institutions is to provide quality education to its students. One way to achieve highest level of quality in higher education system is by discovering knowledge for prediction regarding enrolment of students in a particular course, alienation of traditional classroom teaching model, detection of Unfair means used in online examination, detection of abnormal values in the result sheets of the students, prediction about students’ performance. The paper aims to purpose the use of Data mining techniques to improve the efficiency of higher educational institutions. If data mining techniques such as clustering, dicision tree and association can be applied to higher education processes, it can help improve student’s performance.

DATA MINING IN EDUCATION FOR STUDENTS ACADEMIC PERFORMANCE: A SYSTEMATIC REVIEW

Currently there is an increasing interest in data mining and educational systems, making educational data mining as a new growing research community. Higher education, throughout the world is delivered through universities, colleges affiliated to various universities and some other recognized academic institutes. The main objective of higher education institutes is to provide quality education to its students. Indian education sector has a lot of data that can produce valuable information which can be used to increase the quality of education. Good prediction of student’s success in higher learning institution is one way to reach the higher level of quality in higher education system. In this paper we analyzed the potential use of data mining in education section and survey the most relevant work in this area. Data Mining can be used for dropout students, student’s academic performance, teacher’s performance and student’s complaints. As we know large amount of data is stored in educational database, so in order to get required data and to find the hidden relationship, different data mining techniques are developed & used. Various algorithms and data mining techniques like Classification, Clustering, Regression, Artificial Intelligence, Neural Networks, Association Rules, Decision Trees (CART and CHIAD), Genetic algorithms, Nearest Neighbor method etc. are used for knowledge discovery from databases and helps in prediction of students academic performance. In future work we can apply different data mining techniques on an expanded data set with more distinct attributes to get more accurate results.

REQUISITES OF TOTAL QUALITY MANAGEMENT IN TEACHER EDUCATION

With burgeoning growth of higher education sector in our country and global competition is increasing relentlessly, the need for improving quality of education and employability of our graduates has acquired a new urgency. The aim of this paper is improving the quality of higher education system to meet the demands of the society, quality of academic staff, infrastructure facilities and academic environment. This paper attempts to study the principles underlying total quality management in teacher education system.

Mining Educational Data to Analyze Students Performance

The main objective of higher education institutions is to provide quality education to its students. One way to achieve highest level of quality in higher education system is by discovering knowledge for prediction regarding enrolment of students in a particular course, alienation of traditional classroom teaching model, detection of unfair means used in online examination, detection of abnormal values in the result sheets of the students, prediction about students' performance and so on. The knowledge is hidden among the educational data set and it is extractable through data mining techniques. Present paper is designed to justify the capabilities of data mining techniques in context of higher education by offering a data mining model for higher education system in the university. In this research, the classification task is used to evaluate student's performance and as there are many approaches that are used for data classification, the decision tree method is used here. By this task we extract knowledge that describes students' performance in end semester examination. It helps earlier in identifying the dropouts and students who need special attention and allow the teacher to provide appropriate advising/counseling. Keywords-Educational Data Mining (EDM); Classification; Knowledge Discovery in Database (KDD); ID3 Algorithm.

Basic Problems and Challenges Before the Higher Eduction System in Indian

In an environment of global competitiveness it is important that Indian products of the higher education institutions are as competent as graduates of any other country; not only in their scholastic attainments, but also in terms of the value system and richness of their personality. One another issue relates to the quality of higher education system. It is important to recognize that an important portion of collages and universities are not assessed for quality and therefore we don’t have full picture of the quality and excellence of university and college sector engaged in higher education. Most of colleges and universities are providing traditional courses and study programmes. Some programmes are needful to maintain moral and social values but not all. Hence, there is urgent need of change their courses and restructure of educational programmes in Indian college and university education.