scholarly journals The Investigation of Student Dropout Prediction Model in Thai Higher Education Using Educational Data Mining: A Case Study of Faculty of Science, Prince of Songkla Uni-versity

2019 ◽  
Vol 27 (1) ◽  
pp. 356-367 ◽  
Author(s):  
Jarutas Pattanaphanchai ◽  
Koranat Leelertpanyakul ◽  
Napa Theppalak
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Prediction Model ◽  
Retention Rate ◽  
Dropout Rate ◽  
Drop Out ◽  
Data Mining Technique ◽  
Student Dropout ◽  
The University

The student’s retention rate is one of the challenging issues that representing the quality of the university. A high dropout rate of students affects not only the reputation of the university but also the students’ career in the future. Therefore, there is a need of student dropout analysis in order to improve the academic plan and management to reduce students drop out from the university as well as to  enhance the quality of the higher education system. Data mining technique provides powerful methods for analysis and the prediction the dropout. This paper proposes a model for predicting students’ dropout using the dataset from the representative of the largest public university in the Southen part of Thailand. In this study, data from Faculty of Science, Prince of Songkla University was collected from academic year of 2013 to 2017. The experiment result shows that JRip rule induction is the best technique to generate a prediction model receiving the highest accuracy value of 77.30%. The results highlight the potential prediction model that can be used to detect the early state of dropping out of the student which the university can provide supporting program to improve the student retention rate

scholarly journals Factors Influencing Students’ Decision to Drop Out of Online Courses in Brazil

2020 ◽  
Vol 9 (5) ◽  
pp. 284
Author(s):  
Isabella Moreira Pereira de Vasconcellos ◽  
Diogo Tavares Robaina ◽  
Carole Bonanni
Keyword(s):  
Online Courses ◽  
Dropout Rate ◽  
Drop Out ◽  
Course Content ◽  
Student Dropout ◽  
Educational Professionals ◽  
System Use ◽  
Relevant Variables ◽  
E Learning

In recent years, e-learning has been the fastest growing educational form in students' numbers, and this industry's market revenue (Lee, Choi, &Kim, 2013). Despite this growth, concern about the significantly higher student dropout rate of students in online courses as compared with conventional learning environments has increased. Brazil has also registered a significant increase in the number of students interested in this type of education, but the dropout rate is a considerable concern to institutions. This study’s objective was to identify the relevant variables behind online students’ dropout decision in Brazil. After a literature review that determined the ten most recurrent and relevant variables, we heard professional e-learning experts. They indicated, from their standpoint, what the most pertinent variables influencing dropout would be. Based on this, we conducted a quantitative survey with e-learning students, considering the factors indicated in the literature on this subject and educational professionals’ indications. This study's contribution was to verify that the quality support is extraordinarily relevant and has a high correlation with students' perception of Usefulness, the quality of Course Content, and ease of System Use.

Evaluation of the Academic Setting in Spain 1This study was financed by the University of Oviedo.

1995 ◽  
Vol 11 (2) ◽  
pp. 133-137 ◽  
Author(s):  
Juan Fernández ◽  
Miguel A. Mateo ◽  
José Muñiz
Keyword(s):  
Higher Education ◽  
Decision Making ◽  
Social Climate ◽  
Three Dimensions ◽  
Academic Setting ◽  
Teaching And Research ◽  
Evaluation Questionnaire ◽  
University Teachers ◽  
The University

The conditions are investigated in which Spanish university teachers carry out their teaching and research functions. 655 teachers from the University of Oviedo took part in this study by completing the Academic Setting Evaluation Questionnaire (ASEQ). Of the three dimensions assessed in the ASEQ, Satisfaction received the lowest ratings, Social Climate was rated higher, and Relations with students was rated the highest. These results are similar to those found in two studies carried out in the academic years 1986/87 and 1989/90. Their relevance for higher education is twofold because these data can be used as a complement of those obtained by means of students' opinions, and the crossing of both types of data can facilitate decision making in order to improve the quality of the work (teaching and research) of the university institutions.

scholarly journals Evaluating the performance of teaching staff members, a step towards teaching performance development of higher education in Sebha University

2021 ◽  
Vol 20 (3) ◽  
pp. 21-26
Author(s):  
Zamzam Amhimmid Mare
Keyword(s):  
Higher Education ◽  
Faculty Members ◽  
University Teaching ◽  
Analytic Description ◽  
Teaching Staff ◽  
Teaching Performance ◽  
Staff Members ◽  
Performance Development ◽  
The University

This study aims to show the importance of evaluating the teaching performance level of the University teaching members. It also aims to provide the suggested mechanisms for evaluating the teaching performance of the teaching staff members of Sebha University. This study was based mainly on documents and analytic description to collect information about the importance and ways of evaluating teachers with reference to some of the international experiences on teaching performance development. This study concluded that the absence of an experienced entity that would develop the teaching performance of faculty members is one of the main reasons for the weak teaching performance at Sebha University. Based on the results of the study, it is recommended that there should be a planned system based on measured standards and criteria for evaluating staff members to improve the quality of teaching in the higher education domain. 

scholarly journals Theoretical bases for academics’ potential development: foreign and domestic experience

2021 ◽  
pp. 5-19
Author(s):  
Yurii Skyba ◽  
Hanna Lebedynets
Keyword(s):  
Higher Education ◽  
Teaching And Learning ◽  
The European Union ◽  
Association Agreement ◽  
Intangible Resources ◽  
Quality Of Higher Education ◽  
Potential Development ◽  
Organizational Information ◽  
The University

Ensuring and improving the quality of teaching and learning, in particular the academics’ potential development, is reflected in strategic European and domestic documents, namely in the Association Agreement between Ukraine and the European Union, the Paris Communiqué, the Strategy for Higher Education in Ukraine for 2021-2031 and others. The expediency for academics’ potential development is confirmed by the results of a national survey on the needs for the development of Ukrainian universities in the process of reforming higher education in the context of European integration. The article highlights the problems of academics’ potential development. Based on foreign and domestic experience, the theoretical bases for academics’ potential development, in particular the conceptual and terminological apparatus and structural components of teaching metacompetence are substantiated. The concept «potential of an academic» is defined as a set of intellectual, intangible resources, conditions and opportunities created for the production and accumulation of new knowledge, ideas, technologies, competencies and other productive properties at the university, which combines two levels of connections functioning in unity. The first level of connections are resources that are the result of past and present, and the second – opportunities, i.e. those abilities and connections that are future-oriented, constantly changing, evolving, forming new abilities, characteristics, including elements of the future development. The following components are distinguished in the structure of teaching metacompetence: prognostic; design; objective; innovative; pedagogical partnership; organizational; information and digital; reflexive; linguistic and communicative; inclusive; motivational; health-preserving; emotional-ethical and evaluative-analytical. The development of the above components of teaching metacompetence will help ensure the quality of higher education and increase the competitiveness of the university in the educational services market.

scholarly journals FORMATION AND DEVELOPMENT OF THE INTERNAL SYSTEM OF EDUCATION QUALITY ASSURANCE AT THE UNIVERSITY AS A FACTOR OF STATE SOCIO-ECONOMIC DEVELOPMENT

2020 ◽  
pp. 96-103
Author(s):  
A. Artyukhov
Keyword(s):  
Higher Education ◽  
Economic Development ◽  
Quality Assurance ◽  
Foreign Students ◽  
Education Institution ◽  
The State ◽  
Educational Services ◽  
Socio Economic Development ◽  
The University

The article is devoted to the description and analysis of factors that potentially and actually affect the socio-economic development of the state on the example of the higher education institution. It is established that at the system level the level of ensuring the quality of educational activities and the quality of higher education has a decisive influence on the formation of a positive image of a higher education institution. The results of a survey of students on the criteria for choosing a university to study are presented. Statistics on public funding of education in general and higher education in particular are presented and analyzed. It is established that, despite the formally high percentage of education funding from the level of GDP in absolute terms, the actual funding is low and needs to be strengthened by attracting external funding from customers. Attention is also paid to the state of development of educational services for foreign students. In a competitive environment at the national and international level, the decisive influence on the involvement of foreign students in the university is influenced by the structure of the training program, teacher qualifications, organization of the educational process in the classroom and so on. The article on the example of a higher education institution presents the main stages of formation and development of the internal system of quality assurance of education as an object of influence on the socio-economic development of the state. The development and/or improvement of internal quality assurance systems in universities is becoming a powerful basis for increasing university funding from external (personally involved) sources, reducing the outflow of applicants abroad and the successful provision of educational services to foreign students. At this stage, given the limited opportunities for funding of educational activities by the state (compared to EU countries), the successful implementation of the university development strategy is possible provided that systematic work is done to improve the quality of educational services for domestic and foreign citizens. As part of further research, it is planned to analyze the mutual impact of the education quality assurance system on the effectiveness of scientific activities, the provision of additional paid educational services, training for external customers and other sources.

A Machine Learning Approach to Detect Student Dropout at University

2021 ◽  
Vol 10 (6) ◽  
pp. 3101-3107
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Dropout Rate ◽  
Random Forest Classifier ◽  
Drop Out ◽  
Dropout Rates ◽  
Learning Technology ◽  
Student Dropout ◽  
High Dropout Rate ◽  
Academic Plan

In universities, student dropout is a major concern that reflects the university's quality. Some characteristics cause students to drop out of university. A high dropout rate of students affects the university's reputation and the student's careers in the future. Therefore, there's a requirement for student dropout analysis to enhance academic plan and management to scale back student's drop out from the university also on enhancing the standard of the upper education system. The machine learning technique provides powerful methods for the analysis and therefore the prediction of the dropout. This study uses a dataset from a university representative to develop a model for predicting student dropout. In this work, machine- learning models were used to detect dropout rates. Machine learning is being more widely used in the field of knowledge mining diagnostics. Following an examination of certain studies, we observed that dropout detection may be done using several methods. We've even used five dropout detection models. These models are Decision tree, Naïve bayes, Random Forest Classifier, SVM and KNN. We used machine-learning technology to analyze the data, and we discovered that the Random Forest classifier is highly promising for predicting dropout rates, with a training accuracy of 94% and a testing accuracy of 86%.

HIGHER EDUCATION INSTITUTIONS SUBORDINATE TO THE MINISTRY OF AGRICULTURE-A FORGE OF PERSONNEL FOR THE AGRO-INDUSTRIAL COMPLEX

2020 ◽  
Author(s):  
Ирина Ивановна Широкорад ◽  
Олеся Михайловна Фадеева ◽  
Елена Геннадьевна Пафнутова
Keyword(s):  
Higher Education ◽  
Labor Market ◽  
Education System ◽  
Industrial Complex ◽  
Higher Education System ◽  
Productive Labor ◽  
Level Of Knowledge ◽  
The One ◽  
The University

Система высшего образования развивается не в изоляции. Она находится в непосредственной зависимости от школьной системы и от рынка труда. С одной стороны, образовательные результаты, полученные в университете, зависят от уровня знаний и навыков, которые получили студенты на предыдущем этапе образования, с другой стороны, ожидаемое высокое качество жизни, которое является ключевой мотивацией для поступления в вуз для большинства населения, определяется состоянием и структурой рынка труда. Именно наличие спроса на продуктивную рабочую силу определяет результативность системы высшего образования. The higher education system does not develop in isolation. It is directly dependent on the school system and the labor market. On the one hand, the educational results obtained at the University depend on the level of knowledge and skills that students received at the previous stage of education, on the other hand, the expected high quality of life, which is a key motivation for entering the University for the majority of the population, is determined by the state and structure of the labor market. It is the demand for productive labor that determines the effectiveness of the higher education system.

Englishization of Croatian higher education

2021 ◽  
Author(s):  
Branka Drljača Margić
Keyword(s):  
Higher Education ◽  
Macro Level ◽  
Quality Of Education ◽  
Perceived Benefits ◽  
The Status ◽  
English Medium Instruction ◽  
Micro Level ◽  
The University

The perceived benefits of English-medium instruction (EMI), such as greater competitiveness of universities, are the reasons why meso- and macro-level stakeholders in Croatian higher education (HE) seek to implement it. Nevertheless, the overall adoption of EMI has been rather slow, resulting in only 3% of study programmes in English. Such a small number has sparked no public or scholarly resistance to this aspect of Englishization. On the micro level, however, the introduction of EMI has provoked a range of different reactions, from favourable attitudes to concerns over the quality of education and the status of Croatian in academia. Evidence for these views were gleaned from the studies conducted at the University of Rijeka, Croatia.

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