Critical Success Factors Of E-learning Research Articles

Investigating Critical Success Factors of E-Learning: Different Stakeholders’ Perspectives

Investigating Critical Success Factors of E-Learning: Different Stakeholders’ Perspectives

Identification of Key Performance Indicators through E-Learning Critical Success Factors for an Online Course of English for Football

The main goal of this study was to identify Key Performance Indicators (KPI) through e-learning Critical Success Factors (CSF) for an online course of English for Football in Iran. To this end, the researchers prioritized the e-learning CSFs proposed in the literature from an emic perspective exclusively for the online course of English for Football as a case study. The expert participants in this study were certified football coaching instructors from Iran Football Federation who took an open-ended questionnaire and wrote their statements of success for each CSF and rated them on Analytical Hierarchy Process (AHP) ratio scale through pairwise comparisons. Based on the collected statements of success, the researchers identified KPIs for an e-learning course of English for football. This study resulted in 24 KPIs in line with the CSFs in the literature and the statements of success proposed by the participants of this study. The results of AHP on the CSFs showed that respectively: course, instructor’s characteristics, learner’s characteristics, learning environment, instructional design, support, level of collaboration, knowledge management and technology knowledge were the important CSFs. Finally, the researchers arrived at KPIs based on each ranked CSFs and statements of success. This study could have implications for the ESP curriculum developers and online course organizers to strengthen their course structure by identifying, prioritizing and setting down CSFs and KPIs.

Еxploring e-learning critical success factors in digitally underdeveloped countries during the first wave of the COVID-19

ABSTRACT Regarding the fact that the entire spring semester in higher education was based on online teaching realized at the state University of East Sarajevo, and that the students thus gained a completely new experience, the aim of this research is to identify and study the e-learning critical success factors (CSF) on the basis of the students' perceptions. A number of 356 students of all 17 faculties with in the University participated in the research. The students' attitudes were collected by the instrument containing 36 items, constructed on the basis of a comprehensive review of previous researches of the e-learning critical success factors and semi-structured interview with the students. Seven factors were extracted and studied by the factor analysis: quality learning materials, student's attitude toward e-learning, teacher's attitude toward e-learning, technological support, classroom interaction, student's activities and teacher's attitude towards students. In response to the pandemic, universities are expected to change their traditional concept of learning and offer models of distance learning in the future. Therefore, the results of this research may be of key importance for the selection and implementation of the appropriate e-learning applications and platforms.

Critical Success Factors of eLearning in Distance Education Program in a Developing Country

This paper aims to identify the critical success factors (CSFs) of eLearning in distance education/learning program in a developing country, Bangladesh. Distance education program is accredited in overcoming a number of barriers in education, especially time constraint and geographical location. eLearning is often used as a means of distance education program. In previous researches a number of bottleneck are identified in distance education as well as in eLearning. In Bangladesh, Bangladesh Open University (BOU) is solely authorized to conduct the distance education. The aim of BOU is to distribute the knowledge in remote areas and to the community of unprivileged. BOU has taken the eLearning as the premise of strengthening the distance education program. This study aims to identify the critical success factors (CSFs) that are necessary to ensure the effective distance education through eLearning on the priority basis. As Fuzzy Analytical Hierarchy Process (FAHP) is recognized extensively for identifying the actions required on priority basis, FAHP is used to conduct the study.

Evaluating and Ranking Cloud-Based E-Learning Critical Success Factors (CSFs) Using Combinatorial Approach

Cloud computing has been regarded as one of the significant Information Technology (IT) tools. Many sectors are adopting cloud computing services for its business support. It has also become a new IT paradigm that has transformed the E-Learning system to become more user-friendly. As a result, the E-Learning usage is growing rapidly and being preferred over the conventional teaching-learning process in a big way. This revolutionary change is attributed to the advancement in digital technology. The transformation in digital technology has made the teaching-learning process flexible, easy and convenient for effective knowledge transfer. The cloud-based E-Learning process depends upon many factors of different dimensions that are of significant importance for cloud-based-E-Learning success. Hence they must be studied to successfully analyze their level of importance and fulfill Cloud-based E-Learning positive effectiveness. The current research provides a detailed literature review for cloud-based E-Learning Critical Success Factors (CSFs) of teaching–learning process. Further, the research employs the combinatorial approach to evaluate the diversified dimensions and CSFs of cloud-based E-Learning that helps in quantifying and comparing the influence of various dimensions and CSFs of cloud-based-E-Learning. Four dimensions and fourteen factors have been identified through in-depth literature review and later on evaluated for the prioritization using a combinatorial approach. The influence of such dimensions and factors will help various stakeholders to plan their strategy and resources for the betterment of knowledge transfer through cloud-based-E-Learning.

The contribution of school culture to the learner success factors in e-learning

<p>This study aimed to portray how a school culture contributed to the learner success factors in e-learning in the middle school level. The ethnographic case study design was applied to explore the school culture and the e-learning success factors more deeply and holistically. The data were collected through observations and in-depth interviews. The cross-case analysis was used to interpret the data. The subjects of the study were four students who won in the national e-learning competition and the setting of the institution was in SMP Tentara Genie Pelajar (TGP) in Malang. The fundamental finding of the study, that might not be found in other research, was that the high-academic performance culture of this school gave an indirect contribution to the students’ e-learning success factors, such as the students’ motivation, the students’ e-learning self-efficacy, the students’ prior knowledge on the e-learning technical competency, and the students’ interaction and collaboration. This study gave a big implication because an ethnographic case study on the e-learning critical success factors might be never done in Indonesia before.</p>

E-learning critical success factors: Comparing perspectives from academic staff and students

This article advances knowledge on the factors that lead to successful e-learning in universities, through a comparative study of the perspectives of academic staff and students. In particular, it contributes to the limited knowledge bases on the effectiveness of e-learning in Saudi Arabia, and on the differences in perspectives of different groups of stakeholders in e-learning. Based on previous research, a questionnaire was designed and distributed to convenience samples of academic staff and students at King Saud University, Saudi Arabia. Respondents were invited to express their opinion regarding the importance of a number of factors to the success of e-learning. Principal Component Analysis was conducted on each dataset, in turn, to assess the loading of items onto factors, and the variance explained. The most important finding from this study is that the perspectives of students and academic staff differ, with there being nine factors for academic staff and seven for students. Categories that are common to both groups are: student characteristics, instructor characteristics, ease of access, and support and training. The order for academics is: student characteristics, ease of access, instructor characteristics, and support and training; and, the order for students is: instructor characteristics, student characteristics, support and training, and ease of access.

LearnCube: A Conceptual Framework for E-Learning Implementation in Secondary School

Background/Objectives: E-Learning (EL) enable educators to make use of the internet facilities to deliver their teaching online. Yet, this technology has not been fully explored especially in secondary school. Methods/Statistical Analysis: This paper investigates the effectiveness of implementing EL in a secondary school. Firstly, a theoretical conceptual framework for EL will be proposed. The conceptual framework is essential to ensure that the Critical Success Factors (CSFs) for EL is clearly identified. Next, we modelled the CSF in cube for multi-dimensional analysis. Findings: The outcome of this paper is (i) a conceptual framework for EL implementation which integrates the CSFs and the demographic variables of the personnel involved in the teaching and learning process (for example, teachers and students), and (ii) inter-relationship among the attributed factors. This certainly helps school to adopt EL CSF by overcoming obstacles, and henceforth, it will reduce the failure risk. Application/Improvements: The CSFs are essential to ensure the effective implementation of EL in any organization. From this paper, one can find the suggestion on area to be focused if EL is to be adopted.

APPLIED CLUSTERING ANALYSIS FOR GROUPING BEHAVIOUR OF E-LEARNING USAGE BASED ON MEANINGFUL LEARNING CHARACTERISTICS

One of the critical success factors of e-learning is positive interest of students towards e-learning. The majority of activities of current e-learning usage are viewing and downloading. These activities are not meaningful with regard to enhancing learning quality. Due to that, the aim of this paper is to analyze students’ usage based on meaningful learning characteristics by clustering students’ activities and actions during online learning. We first define meaningful learning characteristics (as those which are active, authentic, cooperative, collaborative, and intentional) and associate these with e-learning activities and actions. Then, we analyze the students’ e-learning usage and define the cluster of student’s meaningful characteristics by using the K-Means cluster method. A case study has been conducted based on the e-learning log files of 37 students on Computational Intelligence Course at the Software Engineering Department, Universiti Teknologi Malaysia. The result of this clustering enables us to determine the students with high ratings on these meaningful activities and actions during online learning. We found out that students with high hits on add, update, and edit are included in the high cluster group. On the contrary, students with high hits on the view actions for all e-learning activities are included in the low cluster group. This result may assist instructors while preparing the strategy of computer usage for education, in terms of providing a greater variety of learning activities, which is applicable for any courses.

E-learning critical success factors: an exploratory investigation of student perceptions

Information Technology (IT) and intense competition are reshaping universities worldwide. Universities have begun to utilise and integrate IT in teaching and learning in order to meet the instructors' and students' needs. E-learning, one of the tools that has emerged from IT, has been integrated into many university programmes. There are several factors that need to be considered while developing or implementing university curriculums that offer e-learning-based courses. Since e-learning is a relatively new learning technology, this paper is intended to identify and measure its Critical Success Factors (CSFs) from student perceptions. In line with the literature, four CSFs were identified and measured, namely, instructor characteristics, student characteristics, technology infrastructure and university support. Student attitude towards using e-learning was empirically tested. A sample of 37 class sections with 538 responses was used to validate the proposed e-learning CSFs. The results revealed that students perceived instructor characteristics as the most critical factor in e-learning success, followed by IT infrastructure and university support. The student characteristics factor was perceived as the least critical factor to the success of e-learning.

Critical success factors for e-learning acceptance: Confirmatory factor models

E-learning, one of the tools emerged from information technology, has been integrated in many university programs. There are several factors that need to be considered while developing or implementing university curriculums that offer e-learning based courses. This paper is intended to specify e-learning critical success factors (CSFs) as perceived by university students. The published e-learning critical success factors were surveyed and grouped into 4 categories namely, instructor, student, information technology, and university support. Each category included several measures. The categorization was tested by surveying 538 university students. The results revealed 8 categories of e-learning CSFs, each included several critical e-learning acceptance and success measures. The level of criticality of each measure was represented by its validity coefficient. Confirmatory factor modeling approach was used to assess the criticality of the measures included in each CSF category.