Assessing and Enhancing Student Experience in Higher Education

2021 ◽  
Author(s):  
Muji Gunarto ◽  
Ratih Hurriyati

Higher education products or services received by students are experiential values. The purpose of this study is how to create the values of student experience so that student satisfaction arises. Higher education should now focus on students by creating strong ties with students and alumni. This research was conducted with a survey confirmatory approach. The survey was conducted at 32 universities in South Sumatra Province, Indonesia with a total sample of 357 students. The sampling technique used was stratified random sampling and data analysis using structural equation modeling (SEM) analysis. The results showed that the values of experience in HE were formed through increased co-creation in HE, where students were directly involved in various campus activities. High co-creation shows that there is a stronger attachment of students to HE and higher value of student experience. Co-creation does not directly affect student satisfaction, but it does indirectly affect experience value. If the value of experience is higher, student satisfaction will also be higher.


2021 ◽  
Vol 11 (20) ◽  
pp. 9543
Author(s):  
Nicolás Matus ◽  
Cristian Rusu ◽  
Sandra Cano

Students’ experiences have been covered by a large number of studies in different areas. Even so, the concept of student experience (SX) is diffuse, as it does not have a widely accepted meaning and is often shaped to the specific purposes of each study. Understanding this concept allows educational institutions to better address the needs of students. For this reason, we conducted a systematic literature review addressing the concept of SX in higher education, specifically aiming at undergraduate students. In this work, we approach the concept of SX from the perspective of customer experience (CX), based on the premise that students are users of higher education institutions’ products, systems and/or services. We reviewed articles published between 2011 and 2021, indexed in five databases (Scopus, Web of Sciences, ACM digital, IEEE Xplore and Science Direct), trying to address research questions concerning: (1) the SX definition; (2) dimensions, attributes and factors that influence SX; and (3) methods used to evaluate the SX. We selected 65 articles and analyzed various SX definitions, as well as scales and surveys to evaluate SX, mainly relating to satisfaction and quality in higher education. We propose a holistic definition of SX and recommend ways to achieve its better analysis.


Author(s):  
UmmeSalma Mujtaba

This chapter sets ground to realize the exceptional significance of students to international branch campuses, which is a popular mode of transnational higher education. Mission statements of different international branch campuses are analyzed that converge on the fact that most of these institutions irrespective of the host country perceive student as their priority. The chapter then moves on to explaining student choice, in a situation where number of international branch campuses co-exist in a home country, such as the case of United Arab Emirates that hosts 19% of the world’s current branch campuses (Observatory, 2012). This information is then employed to expound how international branch campuses can progressively build student experience. Within this chapter, readers can find steps to build student experience in the first year of operation, followed by fine steps that can assist in progressively developing student experience. The chapter then addresses the significance of students in transnational higher education and how this can be developed, leveraged, and converted to be a potent tool such as to ensure sustainable branch campuses (a form of transnational higher education).


Big Data ◽  
2016 ◽  
pp. 1717-1735
Author(s):  
Paul Prinsloo ◽  
Sharon Slade

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.


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