The purpose of this study is to verify the relations between optimal flow experience and learning satisfaction, and between optimal flow experience and effectiveness, in e-Learning environment. The specific major relations are as follows: first, the relation between e-Learning environment and optim...
The purpose of this study is to verify the relations between optimal flow experience and learning satisfaction, and between optimal flow experience and effectiveness, in e-Learning environment. The specific major relations are as follows: first, the relation between e-Learning environment and optimal flow experience, second, the relation between a learner's inclination and optimal flow experience, third, the relation between optimal flow experience and learning satisfaction, effectiveness, fourth, the moderating effect of e-Learning self-efficacy, fifth, the mediating effect of optimal flow experience.
In accordance with the purpose of this study, the hypotheses have been set up as follows:
1. e-Learning environment will predict optimal flow experience.
2. Learner's inclination will predict optimal flow experience.
3. Optimal flow experience will predict learning satisfaction and effectiveness.
4. e-Learning self-efficacy will moderate between optimal flow experience and learning satisfaction, and between optimal flow experience effectiveness.
5. Optimal flow experience will mediate among e-Learning environment, Learner's inclination, learning satisfaction and effectiveness.
In order to verify the hypotheses above mentioned, a questionnaire survey was conducted with the students of a male middle school in Dongduchun, Kyunggi province, Korea. They were learning English through e-Learning environment. Numbers of 300 questionnaires were distributed and valid 239 were collected. They were consisted of 137 first year students and 102 second year students. The data was analysed with various statistical methods such as descriptive statistics, a correlation analysis, simple and multiple regression analysis, and path analysis.
The following are the results of the hypotheses tested in this study.
First, it is verified that the relation between e-Learning environment and optimal flow experience is statistically significant in part. Specifically, optimal flow experience can be predicted by the factors of e-Learning environment variable apart from the factor of learning guidance. In other words, optimal flow experience can be predicted by user friendliness, the presentation method of contents, and unambiguous feedback.
Second, it is verified that the relation between a learner's inclination and optimal flow experience is statistically significant. Specifically, optimal flow experience can be predicted by the factors of a learner's inclination variable. This result implies that optimal flow experience can be predicted by matched challenge and skill levels, clear goals, autotelic learning, perception of ICT media effect, and English learning strategy of a learner's inclination.
Third, it is verified that the relations between optimal flow experience and learning satisfaction, and between optimal flow experience and effectiveness are statistically significant. So that it is to be said that learning satisfaction and effectiveness can be predicted by the factors of optimal flow experience variable.
Fourth, there is no moderating effect of e-Learning self-efficacy between optimal flow experience and learning satisfaction, and between optimal flow experience and effectiveness where both are not statistically significant.
Finally, it is verified that there is a mediating effect of optimal flow experience on the relation of e-Learning environment and learning satisfaction, effectiveness. Also a mediating effect of optimal flow experience occurs on the relation of a learner's inclination and learning satisfaction, effectiveness.
The purpose of this study is to verify the relations between optimal flow experience and learning satisfaction, and between optimal flow experience and effectiveness, in e-Learning environment. The specific major relations are as follows: first, the relation between e-Learning environment and optimal flow experience, second, the relation between a learner's inclination and optimal flow experience, third, the relation between optimal flow experience and learning satisfaction, effectiveness, fourth, the moderating effect of e-Learning self-efficacy, fifth, the mediating effect of optimal flow experience.
In accordance with the purpose of this study, the hypotheses have been set up as follows:
1. e-Learning environment will predict optimal flow experience.
2. Learner's inclination will predict optimal flow experience.
3. Optimal flow experience will predict learning satisfaction and effectiveness.
4. e-Learning self-efficacy will moderate between optimal flow experience and learning satisfaction, and between optimal flow experience effectiveness.
5. Optimal flow experience will mediate among e-Learning environment, Learner's inclination, learning satisfaction and effectiveness.
In order to verify the hypotheses above mentioned, a questionnaire survey was conducted with the students of a male middle school in Dongduchun, Kyunggi province, Korea. They were learning English through e-Learning environment. Numbers of 300 questionnaires were distributed and valid 239 were collected. They were consisted of 137 first year students and 102 second year students. The data was analysed with various statistical methods such as descriptive statistics, a correlation analysis, simple and multiple regression analysis, and path analysis.
The following are the results of the hypotheses tested in this study.
First, it is verified that the relation between e-Learning environment and optimal flow experience is statistically significant in part. Specifically, optimal flow experience can be predicted by the factors of e-Learning environment variable apart from the factor of learning guidance. In other words, optimal flow experience can be predicted by user friendliness, the presentation method of contents, and unambiguous feedback.
Second, it is verified that the relation between a learner's inclination and optimal flow experience is statistically significant. Specifically, optimal flow experience can be predicted by the factors of a learner's inclination variable. This result implies that optimal flow experience can be predicted by matched challenge and skill levels, clear goals, autotelic learning, perception of ICT media effect, and English learning strategy of a learner's inclination.
Third, it is verified that the relations between optimal flow experience and learning satisfaction, and between optimal flow experience and effectiveness are statistically significant. So that it is to be said that learning satisfaction and effectiveness can be predicted by the factors of optimal flow experience variable.
Fourth, there is no moderating effect of e-Learning self-efficacy between optimal flow experience and learning satisfaction, and between optimal flow experience and effectiveness where both are not statistically significant.
Finally, it is verified that there is a mediating effect of optimal flow experience on the relation of e-Learning environment and learning satisfaction, effectiveness. Also a mediating effect of optimal flow experience occurs on the relation of a learner's inclination and learning satisfaction, effectiveness.
주제어
#optimal flow experience
#e-Learning environment
#learner's inclination
#e-Learning self-efficacy
#learning satisfaction
#learning effectiveness
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