Using the HOT-fit model to predict the determinants of E-learning readiness in higher education: a developing Country’s perspective

E-learning readiness has been initiated in higher education institutions (HEI) as an attempt to improve institutions’ service delivery. Meeting and managing the expectations of students using e-learning systems to facilitate teaching and learning activities is a prominent way to make HEI competitive...

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Bibliographic Details
Published in:Education and information technologies 2019-11, Vol.24 (6), p.3555-3576
Main Authors: Mirabolghasemi, Marva, Choshaly, Sahar Hosseinikhah, Iahad, Noorminshah A.
Format: Article
Language:English
Subjects:
Analysis
College Students
Computer Appl. in Social and Behavioral Sciences
Computer Science
Computers and Education
Developing countries
Education
Education parks
Education, Higher
Educational Technology
Electronic Learning
Foreign Countries
Higher education
Influences
Information Systems Applications (incl.Internet)
LDCs
Learning strategies
Methods
Online education
Online instruction
Private Colleges
Program Effectiveness
Readiness
School facilities
Self Efficacy
Student Attitudes
Teaching Methods
User Interfaces and Human Computer Interaction
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Summary:E-learning readiness has been initiated in higher education institutions (HEI) as an attempt to improve institutions’ service delivery. Meeting and managing the expectations of students using e-learning systems to facilitate teaching and learning activities is a prominent way to make HEI competitive. The purpose of this study is to investigate the impact of human, organizational, and technological factors on students’ e-learning readiness. This study was conducted by using a survey method in a private university in the north region of Iran with a total number of 153 respondents. Survey data were analyzed using the partial least squares (PLS) method while Smart PLS was used to test the hypotheses and to validate the proposed model. The results indicated that computer self-efficacy, management support, relative advantage, compatibility, and complexity are significant factors that influence students’ e-learning readiness. The findings provide a basis for assessing the determinants of e-learning readiness in developing countries.
ISSN:1360-2357
1573-7608
DOI:10.1007/s10639-019-09945-9