Factors Affecting Social Entrepreneurial Intent: Significance of Student Engagement Initiatives in Higher Education Institutions

2022 ◽  
Vol 18 (2) ◽  
pp. 69-87
Author(s):  
Kavita Chavali ◽  
◽  
Sudha Mavuri ◽  
Omar Durrah ◽  
◽  
...  
Keyword(s):  
Higher Education ◽  
Student Engagement ◽  
Higher Education Institutions ◽  
Factors Affecting ◽  
Entrepreneurial Intent

scholarly journals FACTORS AFFECTING THE CHOICE OF HIGHER EDUCATION INSTITUTIONS BY PROSPECTIVE STUDENTS IN LATVIA

2016 ◽  
Vol 4 ◽  
pp. 422-430 ◽  
Author(s):  
Nadezda Rika ◽  
Jana Roze ◽  
Irina Sennikova
Keyword(s):  
Higher Education ◽  
Secondary School ◽  
Stepwise Regression ◽  
Higher Education Institutions ◽  
Organizational Factors ◽  
Spearman Correlation ◽  
Prospective Students ◽  
Social Psychological ◽  
Factors Affecting ◽  
Comprehensive Knowledge

Because of increasing competition among Latvian higher education institutions (HEIs), the administrators of these institutions are becoming increasingly interested in understanding how their potential students choose their institution. Comprehensive knowledge of consumer behavior allows institutions to become more effective at making good strategic marketing decisions and to better respond to customers’ needs. The purpose of this study is to understand what factors affect the decision of secondary school leavers in choosing a particular higher education provider and the variables that might predict a student’s choice. The research is based on data collected by the means of a survey distributed among final year students of Latvian secondary schools, with 644 responses analyzed using Spearman correlation and stepwise regression analysis. Analysis of four major groups of factors: cultural, social, psychological, and organizational, revealed that psychological and organizational factors are the best predictors of the choice of HEI. These explained 48% of the variance of the dependent variable (R2 = 0.48; F (1; 641) = 293.46; p < 0.001). The results provide details of the factors with great importance to young people of Latvia in choosing their higher education provider. The HEI can use these factors for designing various student attraction strategies, and thus increase their market share and competitiveness.

Is E-Learning a Pro-Active Response to, or Reaction to, Changes in Educational Policy and Patterns of Educational Demand?

2014 ◽  
pp. 253-267
Author(s):  
Allan M. Lawrence ◽  
Peter J. Short ◽  
Deborah Millar
Keyword(s):  
Higher Education ◽  
Educational Policy ◽  
Higher Education Institutions ◽  
Developed Countries ◽  
Quality Factors ◽  
Student Work ◽  
Factors Affecting ◽  
Educational Demand ◽  
E Learning ◽  
The Impact

This chapter reviews and investigates the models and acceptability of E-Learning to the emerging students markets for Higher Education Institutions (HEIs) from the More Developed Countries (MDCs) and seeks to evaluate the differing models of delivery from a practical and a socio-economic perspective. The research also investigates the impact of the shifts in population growth and the subsequent impact upon the levels of demand from students in Less Developed Countries (LDCs) for higher education. In addition, the logistical and quality factors affecting E-Learning are evaluated, looking at the aspects of academic rigour, plagiarism, and the methods of managing the originality and authenticity of student work. Similarly, the research looks at the viability of situations where the education provider may never physically meet the students through the exclusive use of VLEs, and the possible credibility issues that this may present to institutional and awarding body reputations.

Factors Affecting Internationalization Degree of Higher Education Institutions in Portugal and Spain

2018 ◽  
pp. 348-377
Author(s):  
Marina Amorim Sousa ◽  
Tomás Bañegil Palacios ◽  
Beatriz Corchuelo Martínez-Azúa
Keyword(s):  
Higher Education ◽  
Data Collection ◽  
Higher Education Institutions ◽  
Organizational Level ◽  
Levels Of Analysis ◽  
Internationalization Process ◽  
Mean Values ◽  
Factors Affecting ◽  
The Mean ◽  
Degree Of Internationalization

The aim of this study is to evaluate the degree of internationalization of Iberian Higher Education Institutions (HEIs) and the factors that influence their internationalization process. The study begins with the contextualization of the HEI internationalization process through a brief historical synthesis and the establishment of the levels of analysis of this process, to focus, in more detail, the organizational level. To this end, it is supported in an organization dimensions model to define the components of the internationalization process and the data collection by questionnaire. The results were processed for each of its components, and the degree of internationalization was obtained by calculating the mean values of the components total. The study concludes that the Iberian HEIs have an interesting level of internationalization, which is higher for institutions with more than 5.000 students, with simultaneous focus on teaching and research, conferring the master's and doctor's degrees.

Here Be Dragons

Big Data ◽  
2016 ◽  
pp. 1717-1735
Author(s):  
Paul Prinsloo ◽  
Sharon Slade
Keyword(s):  
Higher Education ◽  
Student Engagement ◽  
New Deal ◽  
Learning Analytics ◽  
Higher Education Institutions ◽  
Student Experience ◽  
Open University ◽  
Student Responsibility ◽  
Student Data ◽  
General Data

Learning analytics is an emerging but rapidly growing field seen as offering unquestionable benefit to higher education institutions and students alike. Indeed, given its huge potential to transform the student experience, it could be argued that higher education has a duty to use learning analytics. In the flurry of excitement and eagerness to develop ever slicker predictive systems, few pause to consider whether the increasing use of student data also leads to increasing concerns. This chapter argues that the issue is not whether higher education should use student data, but under which conditions, for what purpose, for whose benefit, and in ways in which students may be actively involved. The authors explore issues including the constructs of general data and student data, and the scope for student responsibility in the collection, analysis and use of their data. An example of student engagement in practice reviews the policy created by the Open University in 2014. The chapter concludes with an exploration of general principles for a new deal on student data in learning analytics.

Leadership Dynamics in Higher Education Institutions in India

2020 ◽  
pp. 309-331
Author(s):  
Siran Mukerji ◽  
Purnendu Tripathi ◽  
Anjana Anjana
Keyword(s):  
Higher Education ◽  
Higher Education Institutions ◽  
Student Mobility ◽  
Multiple Roles ◽  
Ethical Challenges ◽  
Educational Leader ◽  
Centers Of Excellence ◽  
Factors Affecting ◽  
Vice Chancellor ◽  
Major Factors

The network of higher education institutions (HEIs) has grown at a phenomenal rate in post-independence India and poses wide-ranging challenges for educational leadership. There are other important factors that impinge on the functioning of educational leader who is not only a principal, a president, or a vice chancellor. In fact, he or she is an educational leader encompassing multiple roles. The chapter elucidates the present higher education scenario of India. It portrays the nature and extent of internal and external student mobility and the challenges posed therein. It identifies the major factors affecting the HEIs and their employees in the present changing realm by way of a study conducted in the HEIs and highlights the ethical challenges faced by the educational leaders in promoting and transforming the institutions to centers of excellence.

scholarly journals Factors affecting relative efficiency of higher education institutions of economic orientation

2020 ◽  
Vol 25 (1) ◽  
pp. 45-67
Author(s):  
Andrea Arbula Blecich
Keyword(s):  
Higher Education ◽  
Relative Efficiency ◽  
Higher Education Institutions ◽  
Binary Logistic Regression ◽  
Second Phase ◽  
Education Policies ◽  
Design Guideline ◽  
Factors Affecting ◽  
Third Phase ◽  
Proposed Model

This paper investigates the factors that influence the relative efficiency of higher education institutions of economic orientation. The empirical analysis is carried out on 31 higher educational institutions of economic orientation in Croatia, Slovenia and Bosnia and Herzegovina, in three phases. In the first phase, relative efficiency of observed institutions is evaluated for three main areas of their activities: teaching, research and international activity. In the second phase, higher education institutions are clustered based on relative efficiency results of each individual area of their activity. In the last, third phase, key association factors of a particular cluster are determined using univariate binary logistic regression and odds for transition to a more favourable cluster are defined. The results indicate that odds for positioning in the more efficient cluster are higher in public institutions than in private ones, in institutions with more published professional papers, in those with higher expenditures per faculty, the larger number of enrolled students per faculty, as well as in those with more visiting researchers. The proposed model can serve as a design guideline for education policies and as a moderation guideline for national authorities.

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