Critical Success Factors for E-learning: An Indian Perspective

 

Namitha K Cheriyan

 

Centre for Advanced Research & Training

CHRIST (Deemed to be University), Hosur Road

Bangalore, Karnataka, India

[email protected]

 

 

Abstract

 

Being free from the constraints of time and place, the importance of e-learning is increasing in the education system across the globe. This paper attempts to identify the critical factors attributing to the success of e-learning in higher education sector through a student perspective. A questionnaire is constructed based on the previous research. Using a convenience sampling technique, the data is collected from the undergraduate, postgraduate, and doctoral students of CHRIST (Deemed to be University), Bangalore, India. The participants in the survey were invited to provide their views about the importance of a number of factors attributing to different dimensions in the success of e-learning. An exploratory factor analysis is conducted by employing Principal Component Analysis to assess the factor loading of each variable onto different factors. The study identifies five factors as critical in the success of e-learning viz. technological support, e-learning resources, e-learning support and training, characteristics of student, and characteristics of instructor in their order of relative importance with technological support being the most critical factor.

Keywords- e-learning system; critical success factors; higher education; exploratory factor analysis

 

1. Introduction                  

 

The pedagogy and the learning styles have evolved over time and continue to evolve even today given the developments in the technology being used. The educational institutions undergo unprecedented transformations in their teaching-learning practices with the influence of information technology. Such transformations are of significant importance as they add different dimensions to education with the help of electronically mediated tools in order to smoothen and enhance the process of learning [1]. This revolution in educational sector is referred to as e-learning. It refers to the usage of information technology blended with communication technology to enable the access to quality and real-time resources that enrich the teaching-learning systems in educational institutions. It cannot be considered as a mere substitute of the traditional methods of teaching-learning with the help of technology, but reinforces and magnifies the reach of learning [2]. With the growing importance of e-learning, it has been implemented in many educational institutions across the globe [3], which requires huge investments to be made.

The significance of e-learning systems is that they offer learning opportunities beyond the constraints of time and place. They also support to have experiments in teaching-learning by having new approaches to teaching and learning. However, the literature provides that the extent to which these systems are being used by the students are often low, despite of the huge cost involved in putting them in place [4]. There are a number of studies addressing this issue by contributing possible solutions [5]. The studies were also attempted to measure the satisfaction of users with regard to the e-learning platforms [6] [7].

A potential aspect of e-learning which is not widely studied is to identify the critical success factors for e-learning. This essentially relates to the evaluation of the participants’ experience of e-learning which can be used as a benchmark for the enhancement of e-learning systems. Such critical success factors measure the best or essential characteristics of e-learning systems from the perspective of its users attributing to their success. A critical success factor approach to the evaluation of e-learning systems not only produces a vibrant agenda for the management but also enhances the system as such [8].

A limited number of studies has attempted to identify the critical success factors for e-learning. These studies have been done in a broad range of circumstances that include schools [9] and higher educational institutions [10] [11]. The studies also vary significantly based on the country in which they have been conducted. However, empirical attempts are found lacking to identify the critical factors attributing to the success of e-learning systems in India being one of the leaders of developing countries. Therefore, this study attempts to examine and identify the factors affecting the success of e-learning from a student perspective.

 

2. Data and Methodology

 

2.1. The participants

In order to achieve the objectives of the study, a convenience sampling survey was used employing a self-administered questionnaire. The samples selected consist of the undergraduate, postgraduate and doctoral students of CHRIST (Deemed to be University), Bangalore, India. The responses were gathered from 158 students out of which more than half were females (52.53%). Majority of the survey participants were pursuing their Master’s degree and Bachelor degree (89.87%) on years 1 and 2 of their course (69.62%).

 

2.2. Procedures adopted

A questionnaire was designed to collect the relevant data from the population of the study. A number of critical success factors related to e-learning were identified from the literature and used to prepare the questionnaire. These factors were grouped into different categories viz. those related to the instructor’s characteristics, the participant’s characteristics as a student, the role of technology infrastructure available, the importance of online learning resources, and the role of support and training as exhibited in Table 1. Though the critical success factors identified vary from study to study, they possess some common patterns based on which they were categorized. The list of these factors as presented in Table 1 was used as the basis for designing the questionnaire. The fundamental of the designed questionnaire was thirty four five-point Likert-scale statements relating to various aspects of e-learning, for which each participant was asked to express his/her view about their significance as factors contributing to the success of e-learning.

The data is cleaned for missing values and the questionnaires with incomplete responses were removed from the analysis. Descriptive statistics were calculated for the demographic factors to understand the basic nature of the sample considered for the study. Exploratory factor analysis was carried out to identify the factors that are considered as critical in the success of e-learning by the students.

 

Table 1. E-learning critical success factors from literature

 

 

3. Results and Discussions

 

Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's Test of Sphericity were employed in order to ensure that the data collected was suitable and adequate for exploratory factor analysis. Table 2 reports the results of KMO and Bartlett’s Test. From the result of Bartlett's Test of Sphericity, it can be inferred that the correlations between the variables considered in the study, when taken collectively were significant at one percent level. This indicates that there exists non-zero correlations among the variables selected. The table also shows an overall measure of sampling adequacy value of 0.920 which falls in the acceptable range i.e. above 0.50. As both these test are fulfilling the basic assumptions of exploratory factor analysis, the data is deemed suitable for exploratory factor analysis.

 

Table 2. KMO and Bartlett's Test

 

A Principal Component Analysis was employed to find out the factors which explain the most variance in the data used. The Eigenvalues were considered as the criterion to decide the number of factors to be identified along with the cumulative percentage of variance explained. Only those factors which were having Eigenvalue above 1 were extracted. This criterion had provided for five factors from the set of thirty five variables.

Varimax rotation is used to generate the component matrix. As an orthogonal rotation, it ensures that the factors remain uncorrelated throughout the process of rotation. The component matrix displays loading for the rotated factor matrix. The factor loadings represent the extent to which a variable is associated with a factor. The variables were examined for their factor loadings. All the factor loadings were found to be above the value of 0.5. Therefore none of the variables were excluded from the analysis and all the variables were retained with their corresponding factors. As a final step of Exploratory Factor Analysis, the five factors derived were named in such a way that the name reflect the characteristics of the variables loaded to the factor.  Table 3 exhibits the final factors along with the variables loaded onto them. The five factors derived are found to be explaining a total of 78.064% of the variances in the data considered for the study.

 

 

Table 3. Final factors extracted

 

The questionnaire used for the study had five categories to which variables were broadly classified. The results of exploratory factor analysis also provided five factors with almost the same variables loaded to each factor. The factors identified are named as technological support, e-learning resources, e-learning support and training, characteristics of student, and characteristics of instructor.

The factor technological support includes the variables such as accessibility to multimedia technologies, accessibility of online communication tools, adequate computer labs, reliability of technical infrastructure, facility to explore learning material using the e-learning system, speed of internet, easiness in browsing, knowledge and acquaintance about computers, and easy access to internet. Among these variables loaded to the critical success factor viz. technological support, all the variables except the knowledge and acquaintance of the participant about computers was categorised as the role of technology infrastructure available as identified by the literature [10] [12] [13] [14]. This indicates that, in line with the trend across the globe, Indian students also consider technological support as one of the most critical factor in the success of e-learning system in the country. Though the variable the knowledge and acquaintance of the participant about computers was initially categorised as participant’s characteristics as a student, its loading to the technological support is reliable as it is also related to the technological aspect. Accessibility to multimedia technologies and easy access to internet are found to be having the maximum and minimum association with the factor technological support (83.4% and 60.4%).

The variables viz. interaction of the course, accessibility to the e-learning resources while being in and out of the campus, adequacy of communication with the instructor in the e-learning system, adequacy of the learning materials provided, the design and layout in which the information is provided, easiness in registration for the e-learning course, accessibility to and adequacy of online test/quizzes, and possibility to return to uncompleted tasks which were initially categorized as the importance of online learning resources are loaded to one common factor which is renamed as e-learning resources. Among these eight variables, interaction of the course is found to be recognized by the students as highly associated with the factor (77.6%) followed by accessibility to the e-learning resources while being in and out of the campus (77.2%).

The third critical success factor explored from the exploratory factor analysis is e-learning support and training with six variables viz. adequacy of training sessions on the usage of e-learning systems, openness and sociability of the support team, accessibility to the online help desk, availability of offline technical support, up-to-dateness of the learning materials, and ability to measure the progress of learning, loaded to it. Among these the first four were initially categorized as the role of support and training whereas the last two were categorized originally as the importance of online learning resources but loaded to e-learning support and training. However, the misclassification of the last two variables can be validated with the help of correlation matrix of the variables used in the study which exhibits statistically high correlation of the up-to-dateness of the learning materials and ability to measure the progress of learning with the variables representing support and training aspects. On the other hand, the loadings of adequacy of training sessions on the usage of e-learning systems, openness and sociability of the support team, accessibility to the online help desk, and availability of offline technical support to the e-learning support and training factor can be supplemented with the literature [11] [12] [15] [16].

The readiness to take part in e-learning, learning style, aptitude to find topics in e-learning system, the extent of satisfaction while using technology, and understanding about the use of various parts of the e-learning systems which were categorized as the participant’s characteristics as a student as identified from the literature are loaded together to form a new factor [10] [11] [13]. As all these variables are focused towards the same dimension, it is renamed considering their original categorization as characteristics of student. Among these student characteristics, his/her readiness to take part in e-learning is found to be having the maximum association with the factor (76.2%) followed by the learner’s style of learning (74.8%). Understanding about the use of various parts of the e-learning systems is identified as the least associated variable (65.8%).

The fifth and the last critical success factor identified from the study is named as characteristics of instructor as all the variables initially categorized as those related to the instructor’s characteristics are loaded to this factor. They include the clarity of instructor’s explanation, the style of teaching of the instructor aiding e-learning technologies, capability of the instructor for using the e-learning system efficiently, ability of the instructor to motivate his/her students, the approachability of instructor in general and during teaching, and enthusiasm of the instructor while teaching aiding e-learning tools. However, the loading of these variables to the factor is comparatively lower with a maximum value of 69.9% for the clarity of instructor’s explanation and the minimum value of 60.5% for enthusiasm of the instructor while teaching aiding e-learning tools. Comparing this with the factor loadings for the previous factors, it can be inferred that rather than the characteristics of the instructor, it is the technological support, the availability of e-learning resources, and e-learning support and training are critical in the success of e-learning systems in Indian higher education sector though demands for empirical confirmation.

Finally, Table 4 presents the relative ranking of critical success factors for e-learning among the students pursuing higher education in India. The most important three critical success factors (in order of importance reflected by the percentage variance they explain) are technological support, e-learning resources, and e-learning support and training. This empirically confirms the significantly high factor loadings of the variables onto these factors.

 

Table 4. Total variance explained

 

The factors presented in Table 4 are regarded as the most important factors for the success of e-learning as identified by the students pursuing higher education in India with special reference to CHRIST (Deemed to be University). This is a substantial indicator of their perspective on e-learning systems. For instance, the participants who are students, prioritizing the technology infrastructure, consider technological support and the e-learning resources as important over other factors. In other words, while they acknowledge the importance of their own characteristics or the characteristics of instructors, they regard the technological support and the e-learning resources as of prime importance as this system of learning cannot exist and grow without the most suitable and relevant technology and learning resources rather than the instructor.

The critical success factors identified in this study are unique, like many other earlier studies. There are a good number of studies attempted to identify the factors critical for the success of e-learning, but these factors vary substantially from a study to another. For instance, ref. [10] acknowledged seven different factors with three derived from the characteristics of students. The remaining four are technology, characteristics of instructor, e-learning system being followed, and the support system in place. On the other hand, ref. [9] identified just four factors viz. the characteristics of students, characteristics of the instructor, the technology in use, and the content and design. Even though there are a number of persistent factors identified in different studies, there lacks a consensus on the number of factors critical for the success of e-learning. This study is of no difference. It suggests five factors among which majority are identified as important individually in different papers. The potential reasons for such differences can be attributed to the differences of studies in terms of their objectives, nature, approach, environment in which they are conducted, and so on. Further, if there is any consensus on the number of factors and their categories, their relative importance may differ from study to study. Therefore, as a whole, there is an ample scope for future research to identify the critical success factors for e-learning. The further studies in Indian context can be attempted to identify the critical success factors for e-learning from the instructors’ point of view. Attempts can also be made to model the factors critical for the success of e-learning which can be generalized.  

 

5. Conclusion

 

This study attempted to identify the critical success factors for e-learning in Indian higher education sector with special reference to the students of CHRIST (Deemed to be University), Bangalore, India. Using a convenience sampling technique, data is collected from 158 respondents and the exploratory factor analysis is employed to identify the important categories of factors critical for the success of e-learning in Indian context. It reports five factors viz. technological support, e-learning resources, e-learning support and training, characteristics of student, and characteristics of instructor as critical for the success of e-learning in their order of importance as identified by the students pursuing various higher educational courses ranging from undergraduate programmes to doctoral programmes.

The study contributes significantly to the existing literature as it identifies the factors that can have impact on the success of e-learning. This is of immense use for the policy makers in such a way that this provides first-hand information about the areas to be focused to make e-learning successful in the country’s higher education sector. It enables to design and implement the e-learning system in a better way and to have systematic investments in e-learning. This systematic approach not only saves the resources of educational institutions in terms of labour, money, and time but also enhances the image of such institutions [9]. Therefore, it is suggested to focus on these factors before designing new e-learning systems or while improvising or enhancing the existing e-learning system.

References

 

[1] Piccoli, G., Ahmad, R., & Ives, B. (2001). Web-based virtual learning environments: A research framework and a preliminary assessment of effectiveness in basic IT skills training. MIS quarterly, 401-426.

[2] Islam, A. N., & Azad, N. (2015). Satisfaction and continuance with a learning management system: Comparing perceptions of educators and students. The International Journal of Information and Learning Technology, 32(2), 109-123.

[3] Garrison, D. R. (2011). E-learning in the 21st century: A framework for research and practice. Routledge.

[4] Bhuasiri, W., Xaymoungkhoun, O., Zo, H., Rho, J. J., & Ciganek, A. P. (2012). Critical success factors for e-learning in developing countries: A comparative analysis between ICT experts and faculty. Computers & Education, 58(2), 843-855.

[5] King, E., & Boyatt, R. (2015). Exploring factors that influence adoption of e‐learning within higher education. British Journal of Educational Technology, 46(6), 1272-1280.

[6] González-Gómez, F., Guardiola, J., Rodríguez, Ó. M., & Alonso, M. Á. M. (2012). Gender differences in e-learning satisfaction. Computers & Education, 58(1), 283-290.

[7] Teo, T., & Wong, S. L. (2013). Modeling key drivers of e-learning satisfaction among student teachers. Journal of Educational Computing Research, 48(1), 71-95.

[8] Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful e-Learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & education, 50(4), 1183-1202.

[9] Taha, M. (2014). Investigating the success of E-learning in secondary schools: The case of the Kingdom of Bahrain (Doctoral dissertation).

[10] Selim, H. M. (2007). E-learning critical success factors: an exploratory investigation of student perceptions. International Journal of Technology Marketing, 2(2), 157-182.

[11] Puri, G. (2012). Critical success Factors in e-Learning–An empirical study. International Journal of Multidisciplinary Research, 2(1), 149-161.

[12] Masrom, M. B. (2008). Critical success in e-learning: an examination of technological and institutional support factors. International Journal of Cyber Society and Education, 1(2), 131-142.

[13] Musa, M. A., & Othman, M. S. (2012). Critical success factor in e-Learning: an examination of technology and student factors. International Journal of Advances in Engineering & Technology, 3(2), 140.

[14] Ahmed, T. T. (2013). Toward Successful E-Learning Implementation in Developing Countries: A Proposed Model for Predicting and Enhancing Higher Education Instructors' Participation. International Journal of Academic Research in Business and Social Sciences, 3(1), 422.

[15] Menchaca, M. P., & Bekele, T. A. (2008). Learner and instructor identified success factors in distance education. Distance education, 29(3), 231-252.

[16] Alhomod, S., & Shafi, M. M. (2013). Success Factors of E-Learning Projects: A Technical Perspective. Turkish Online Journal of Educational Technology-TOJET, 12(2), 247-253.