E-learning has been around for more than ten years, and now it is widely regarded as a viable option for a variety of educational contexts. E-learning provides a new set of tools that can add value to traditional leaning mode, such as accessibility to...
E-learning has been around for more than ten years, and now it is widely regarded as a viable option for a variety of educational contexts. E-learning provides a new set of tools that can add value to traditional leaning mode, such as accessibility to content, efficient management of courseware and learners, and enhanced delivery channels.
Despite the rapid growth of e-learning, this quantitative growth has not always guaranteed the quality of learning. Especially, learners participating in cyber university are most likely to have their own job tasks to perform, which makes it difficult for learners to concentrate on learning itself.
To improve learning outcomes, there has to be an understanding of relationships of learning outcome variables and variables which affect learning outcomes. Thus, present study investigates the structural relationship among self-efficacy, intrinsic value, test anxiety, instructional design, flow and achievement. Based on the literature review, self-efficacy, intrinsic value, test anxiety have been chosen as a motivation variables, instructional design as a learning environment variable, and flow and achievement have been chosen as a outcome variables.
The Research questions are:
1. Do motivation variables(self-efficacy, intrinsic value) and instructional design have direct effects on learners’flow?
2. Do motivation variables(self-efficacy, intrinsic value, test anxiety), instructional design, and flow have direct effects on learners’achievement?
3. Do flow have mediator effects on the relationship between motivation variables(self-efficacy, intrinsic value), instructional design and learners’achievement?
Two online surveys were administered in H cyber university who enrolled "computer application". 963 Participants went through this course and answered the survey but, 4 respondents who did not complete their surveys were excluded. A total of 959 cases were analyzed for this research.
For statistical analysis, descriptive statistics, exploratory factor analysis, correlation analysis, confirmative factor analysis, structural equation modeling analysis and Sobel’s test were used.
The major findings of this study are as follows.
First, self-efficacy, instructional design had statistically significant direct effects on learning flow. That is, learners are likely to experience flow during learning, when they have higher self-efficacy when they perceive the e-learning courseware well-designed and easy to use.
Second, self-efficacy, intrinsic value, flow had statistically significant direct effects on achievement. That is, when learner's try to learn for their own sakes' with belief what they can accomplish their learning task successfully, and when they experience flow during learning, learners' achievement will be improved.
Third, the result indicated that learning flow was a meaningful mediator between self-efficacy, instructional design and achievement. That is consistent with the results from the prior research reporting learning flow as an influential factor for learning outcome.
Based on the results of this study, further research is suggested as follows.
First, the direct effect of test anxiety to achievement was not significant, which is still controversial in previous research. Thus, the role of test anxiety to achievement has to be analyzed in multidimensional aspects.
Second, results of relationship between instructional design and flow can be applied only to the Korean cyber university setting. In order to generalize the model, sample for the future study could be selected from other countries or various learning contexts.
Lastly, the effect of intrinsic value to flow and achievement should be examined in various contexts.