scholarly journals DISCUSSION ON THE QUALITY OF EUROPEAN HIGHER EDUCATION SYSTEMS USING CLUSTER ANALYSIS

2018 ◽  
Author(s):  
Romana Provazníková ◽  
Denisa Chlebounová
Keyword(s):  
Higher Education ◽  
Cluster Analysis ◽  
Education Systems ◽  
Higher Education Systems ◽  
European Higher Education

scholarly journals Quality Assessment of Online Learning in Regional Higher Education Systems

2021 ◽  
Vol 17 (3) ◽  
pp. 929-943
Author(s):  
Olga A. Gritsova ◽  
Elena V. Tissen
Keyword(s):  
Higher Education ◽  
Online Learning ◽  
Online Education ◽  
Quality Assessment ◽  
Student Satisfaction ◽  
Educational Process ◽  
Learning Mechanisms ◽  
Education Systems ◽  
Higher Education Systems

The quality of online learning mechanisms, widely implemented due to the COVID-19 pandemic, is a significant issue for regional higher education systems. The research aims to assess student satisfaction with the quality of online education by identifying discrepancies between their requirements and the actual learning process. In order to examine the gaps between students’ expectations and perceptions, a new approach was proposed based on the integrated use of Gap analysis and SERVQUAL methodology, combining qualitative and quantitative aspects. SERVQUAL questionnaires for measuring student satisfaction with online learning include the following criteria: tangibles, reliability, responsiveness, assurance, empathy. Full- and part-time undergraduates of humanitarian and socio-economic departments of two universities participated in the study. Ural Federal University bachelors, learning via Moodle and Microsoft Teams platforms, could directly communicate with their peers and professors, while students of National Research Nuclear University MEPhI were engaged in massive open online courses (MOOC). As a result, all five criteria were analysed in the proposed model for quality assessment of online learning to reveal the gaps between students’ expectations and perceptions of the educational process. Significant discrepancies in the «empathy» and «responsiveness» criteria in both groups demonstrate low student satisfaction with the quality of communication and individualisation of learning. The research findings can be used to construct resource allocation models for implementing educational programmes and developing support measures for regional higher education institutions.

scholarly journals Challenges to Higher Education in Laos and Cambodia

2019 ◽  
pp. 20-21 ◽  
Author(s):  
Martin Hayden
Keyword(s):  
Higher Education ◽  
Public Sector ◽  
Higher Education Institutions ◽  
Education Sector ◽  
Private Higher Education ◽  
Institutional Autonomy ◽  
Education Systems ◽  
Higher Education Systems

The higher education systems in Laos and Cambodia have been expanding rapidly over recent years, but with increasing reliance on a teaching-only private higher education sector, the quality of which is extremely variable. Public-sector higher education institutions, though generally considered more prestigious to attend, are severely constrained by a lack of institutional autonomy and limited budgets, and so their quality is also a matter for concern.

Instructor Performance Prediction Model Using Artificial Intelligence for Higher Education Systems

2021 ◽  
Author(s):  
Shuping Xiao ◽  
A. Shanthini ◽  
Deepa Thilak
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Decision Making ◽  
Prediction Model ◽  
Education Systems ◽  
Higher Education Systems ◽  
Routine Tasks ◽  
Instructor Performance ◽  
The Individual

Recent advancements in Artificial Intelligence techniques, including machine learning models, have led to the expansion of prevailing and practical prediction simulations for various fields. The quality of teachers’ performance mainly influences the quality of educational services in universities. One of the major challenges of higher education institutions is the increase of data and how to utilize them to enhance the academic program’s quality and administrative decisions. Hence, in this paper, Artificial Intelligence assisted Multi-Objective Decision-Making model (AI-MODM) has been proposed to predict the instructor’s performance in the higher education systems. The proposed AI-assisted prediction model analyzes the numerical values on various elements allocated for a cluster of teachers to evaluate an overall quality evaluation representing the individual instructor’s performance level. Instead of replacing teachers, AI technologies would increase and motivate them. These technologies would reduce the time necessary for routine tasks to enable the faculty to focus on teaching and analysis. The usage for administrative decision-making of artificial intelligence and associated digital tools. The experimental results show that the suggested AI-MODM method enhances the accuracy (93.4%), instructor performance analysis (96.7%), specificity analysis (92.5%), RMSE (28.1 %), and precision ratio (97.9%) compared to other existing methods.

ICT in Legal Education

2009 ◽  
Vol 10 (6-7) ◽  
pp. 669-716 ◽  
Author(s):  
Antoinette J. Muntjewerff
Keyword(s):  
Higher Education ◽  
Legal Education ◽  
Education Institution ◽  
Education Systems ◽  
European Higher Education Area ◽  
Bologna Declaration ◽  
Staff Members ◽  
Higher Education Systems ◽  
Internal Mobility ◽  
European Higher Education

The Bologna Declaration (1999) started a process of reforming European higher education. The major aim of the declaration was to construct a single European Higher Education Area by 2010,“‥through increased compatibility and comparability of higher education systems in order to facilitate internal mobility for students, graduates and higher education institution staff members, but also to make European higher education more recognisable and attractive to students and scholars from outside Europe.”

Sign in / Sign up

Export Citation Format

Share Document