An Analysis of Factors that Affected e-Learning of Students at Public Universities in Bangkok Metropolitan Area

Kalayanee Jitgarun
Sangdeun Thaveesin
Jariya Neanchaleay
Surachai Suksakulchai
Bundit Puthaserenee
Thailand

The purposes of this research were to analyze and to describe the major factors that affected e-Learning of students at public universities in Bangkok metropolitan area. The sample chosen for this study were 1,014or 97.5 % out of 1,040 students at the Faculty of Education of public universities in Bangkok metropolitan area.

The instrument used for data collection was 7 rating scales. The reliability of the instrument, calculated by Cronbach Alpha Coefficient is 0.92. The data was analyzed by using the means (X), Standard Deviation (S.D.) and Analysis of Factors by Principal Component Analysis technique: PCA, orthogonal rotation axis by Varimax Method.

The results of the study were as follows:
1. There were 14 major factors that affected e- Learning of students at public universities in Bangkok metropolitan area as follows: 1) virtual lesson, 2) promptness of network system as well as the students' readiness, 3) useful learning, 4) feeling of persons and interesting lessons, 5) supporting thought system and equity of education, 6) supporting from the institutes, 7) personal status, 8) anyplace, anytime for education, 9) social value and the acceptance of innovation, 10) experienced and facilitated by others concerned, 11) supporting self-learning and 12) finding out knowledge and enhancing English language. These factors could be explained 63.551 % of the total variance.

2. A study of Correlation Coefficient between 12 and 52 factors was 0.390 - 0.779 and Correlation Coefficient between 12 factor with that affected e- Learning was 0.438 - 0.863, which was in high level. Correlation Coefficient within the internal factors of 12 was of 0.005 - 0.070, which was in low level.
3. The regression or predicting equation that affected e-Learning of students at public universities in Bangkok metropolitan area was :

Y = Z + 0.673 (Virtual) + 0.843(Network) + 0.863(Useful) + 0.657(Interesting) +0.701(Thought) + 0.623(Supporting) +0.598(Status) + 0.706(Any place/time) +0.737(Value) + 0.820(Experience) + 0.650(Learning) + 0.438(Knowledge)

The predicting equation has the power of prediction 82.857 % and the error of predicting was 7.143

Here, e-Learning is defined as any use of technology for learning outside the boundaries of the physical classroom. Also, e-Learning, referred to as Web-based training, is anywhere, anytime, self-paced instruction that is presented over the Internet to browser-equipped learners and to meet the needs of today's life-long learners. Thus, with e-Learning we can empower learners, and the learner, as well as the mentoring system, is held accountable. What's more, e-Learning provides a new set of tools that can add value to all the traditional learning modes-classroom experiences, textbook study, CD-ROM, and traditional computer based training. However, e-Learning will not replace the classroom setting, but enhance it, taking advantage of new content and delivery technologies to enable learning. The ultimate objective of the e-learning portal is to increase and facilitate access to education resources in different regions of the world in different languages while stimulating professional cooperation to improve the quality of education and learning.

 
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