scholarly journals Factors Affecting Students' Acceptance of e-Learning System in Higher Education

2020 ◽  
Vol 5 (2) ◽  
pp. 54-65
Author(s):  
Nurhafizah Ahmad ◽  
Norazah Umar Umar ◽  
Rozita Kadar ◽  
Jamal Othman
Keyword(s):  
Higher Education ◽  
Learning Style ◽  
Main Idea ◽  
Learning System ◽  
Independent Learning ◽  
Online Questionnaire ◽  
Factors Affecting ◽  
Effective Learning ◽  
Significant Relationships ◽  
E Learning

e-Learning has become the most important supporting tool offering independent learning style among students. The main idea of this paper is to dismantle and analyse factors that influence the acceptance of e-Learning among students in higher education.  An online questionnaire link was distributed to a sample comprising 123 respondents. Significant relationships and strength of relationship were observed between the e-Learning acceptance, quality, e-Learning self-efficacy, enjoyment, accessibility, and computer playfulness. The findings showed that all factors were positively correlated to the e-Learning system except the enjoyment of e-learning that did not affect the acceptance of e-learning. Conclusively, all factors stated were considered the main criteria in designing effective e-learning system. Future works such as embedding and integrating multimedia elements in the e-learning system will be additional attraction to learners and instructors for the effective learning style.

Factors Affecting Successful Adoption and Adaption of E-Learning Strategies

2021 ◽  
pp. 19-35
Author(s):  
Enis Elezi ◽  
Christopher Bamber
Keyword(s):  
Higher Education ◽  
Learning Strategies ◽  
Creative Thinking ◽  
Teaching And Learning ◽  
Higher Education Institutions ◽  
Action Learning ◽  
Independent Learning ◽  
Factors Affecting ◽  
E Learning ◽  
The Impact

This chapter explores factors affecting the development of e-learning strategies in the context of higher education institutions. The authors focus on understanding the impact of e-learning on pedagogical approaches to teaching and learning and elaborate on the challenges higher education institutions experience in implementing e-learning strategies. A combination of synchronous and asynchronous delivery allows educational establishments to not only offer a service that is good value for money but promotes action learning, and encourages ownership, independent learning, and creative thinking. This work proposes social networking scaffolding for asynchronous and synchronous e-learning, where the learner is at the centre of a social network system. Furthermore, the chapter provides guidance to higher education governors, leaders, and e-learning technicians in developing and implementing e-learning strategies.

Artificial Intelligence Applications with e-Learning System for China’s Higher Education Platform

2021 ◽  
Author(s):  
Xiaoran Fu ◽  
K. Lokesh Krishna ◽  
R. Sabitha
Keyword(s):  
Artificial Intelligence ◽  
Higher Education ◽  
Student Learning ◽  
Learning Style ◽  
Adaptive Learning ◽  
Teaching Quality ◽  
Learning System ◽  
Learning Context ◽  
E Learning ◽  
Student Learning Style

Artificial Intelligence (AI) assisted educational institutions extensively utilize electronic learning context to guarantee improved teaching and learning experiences accompanied by educational activities. E-learning or online learning plays a significant role in Chinese higher education. There is a challenge to implement e-learning in China’s higher education to improve course resources, student learning style prediction, teaching quality, and service support. Hence in this paper, Artificial Intelligence based Efficient E-learning Framework (AI-EELF) has been proposed to overcome the challenges faced by China’s higher education while implementing e-learning modules. The collected student data can be efficiently utilized and exploited to progress in an adaptive learning environment. The proposed AI-EELF method introduces multiple learning models to enhance teaching quality and predict the student learning style. The experimental results show that the proposed AI-EELF achieves high performance, prediction ratio in determining students’ learning style and improves teaching quality compared to other existing methods.

Toward a Hybrid Recommender System for E-learning Personnalization Based on Data Mining Techniques

2018 ◽  
Vol 2 (4) ◽  
pp. 271 ◽  
Author(s):  
Outmane Bourkoukou ◽  
Essaid El Bachari
Keyword(s):  
Learning Style ◽  
Recommender System ◽  
Adaptive Learning ◽  
Learning Objects ◽  
Research Field ◽  
Learning System ◽  
K Nearest Neighbors ◽  
E Learning ◽  
Hybrid Recommender System ◽  
Hybrid Recommender

Personalized courseware authoring based on recommender system, which is the process of automatic learning objects selecting and sequencing, is recognized as one of the most interesting research field in intelligent web-based education. Since the learner’s profile of each learner is different from one to another, we must fit learning to the different needs of learners. In fact from the knowledge of the learner’s profile, it is easier to recommend a suitable set of learning objects to enhance the learning process. In this paper we describe a new adaptive learning system-LearnFitII, which can automatically adapt to the dynamic preferences of learners. This system recognizes different patterns of learning style and learners’ habits through testing the psychological model of learners and mining their server logs. Firstly, the device proposed a personalized learning scenario to deal with the cold start problem by using the Felder and Silverman’s model. Next, it analyzes the habits and the preferences of the learners through mining the information about learners’ actions and interactions. Finally, the learning scenario is revisited and updated using hybrid recommender system based on K-Nearest Neighbors and association rule mining algorithms. The results of the system tested in real environments show that considering the learner’s preferences increases learning quality and satisfies the learner.

Developing a Framework to Evaluate E-learning System at Higher Education in Indonesia

2020 ◽  
Author(s):  
Meilia Agatha Priska ◽  
Dilla Aulia ◽  
Erlinda Muslim ◽  
Lidya Marcelina
Keyword(s):  
Higher Education ◽  
Learning System ◽  
E Learning

Higher education student engagement in times of pandemic: the role of e-learning system usability and teacher behavior

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Khalid Abed Dahleez ◽  
Ayman A. El-Saleh ◽  
Abrar Mohammed Al Alawi ◽  
Fadi Abdelmuniem Abdelfattah
Keyword(s):  
Higher Education ◽  
Student Engagement ◽  
Cognitive Engagement ◽  
Teacher Behavior ◽  
Learning System ◽  
Emotional Engagement ◽  
Education Student ◽  
Content Type ◽  
System Usability ◽  
E Learning

PurposeThis research examined the factors affecting several types of student engagement, namely agentic, behavioral, emotional and cognitive engagement. Specifically, it examined the effect of e-learning system usability on student engagement and explored teacher behavior's possible intervening impact on this relationship.Design/methodology/approachData were collected from 418 students studying at different specializations at Omani private academic institutions. This study employed a quantitative methodology and utilized the Smart-PLS for data analyses.FindingsThe findings showed that e-learning system usability influenced significantly and positively agentic, behavioral and cognitive engagement. However, the link between e-learning system usability and emotional engagement was not significant. Moreover, teacher behavior mediated the relationship between e-learning system usability and the four types of engagement.Originality/valueThis study improves one’s understanding of how the interaction of e-learning system usability and teacher behavior affects several aspects of student engagement. It also helps higher education administrators and policymakers by exploring the influential effects of e-learning systems usability and teacher behavior on facilitating students' engagement.

scholarly journals Factors affecting student interest in web-based learning in higher education

2020 ◽  
Vol 6 (1) ◽  
pp. 57-60
Author(s):  
Leni Pebriantika ◽  
Ade Vidianti ◽  
Johan Eka Wijaya ◽  
Leni Pebriantika
Keyword(s):  
Higher Education ◽  
Teaching Style ◽  
Independent Learning ◽  
Student Interest ◽  
Teaching Materials ◽  
Web Based ◽  
Factors Affecting ◽  
Web Based Learning ◽  
Use Of Technology ◽  
The Times

Technology has an important role in improving the quality of education. Learning that is supported by technological devices today seems obligatory to be used in line with the times. Even more varied learning that leads to independent learning for students. Independent learning for students requires teaching materials that can facilitate students in learning, one of which is web-based teaching materials. Web-based learning has been widely implementing in education. The purpose of this study is to determine the factors that influence student interest in web-based learning in higher education using case studies. So that the data and information obtained can later be used as a foundation in the application of web-based learning that is more interesting and better than. This research is descriptive qualitative research with a case study. Factors that influence students' asking for web-based learning are: Web-based teaching materials are more comfortable to learn without having to print. The use of technology enables students to access knowledge anytime and anywhere. Interactions that occur in Web-based learning are more attractive, which allows students to be able to consult with lecturers at any time. The interface of web-based learning is exciting and not dull. Other factors can be sourced from the teaching style of lecturers, and so on. From several factors that influence student interest, it is also found that web-based learning can change the character of student learning more independently and more timely in the following knowledge and doing assignments given by lecturers.

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.

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