E-learning experience: Modeling students’ e-learning interactions using log data

Authors : Sinan KESKİN, Halil YURDUGÜL

Pages : 1-13

Doi:10.31681/jetol.938363

View : 37 | Download : 12

Publication Date : 2022-01-31

Article Type : Research Paper

Abstract :This study aims to examine e-learning experiences of the learners by using learner system interaction metrics. In this context, an e-learning environment has been structured within the scope of a course. Learners interacted with learning activities and leave various traces when they interact with others, contents, and assessment tasks. Log data were formed on these e-learning interactions. In the data analysis phase, firstly, a data pre-processing was performed, and then confirmatory factor analysis insert ignore into journalissuearticles values(CFA); was used to test how well the measured learning activity variables represent the latent system component variables. Then it was tested whether these components compose a latent e-learning experience variable insert ignore into journalissuearticles values(second-order CFA);. The results showed that the learners interacted with five different system components: hypertext, the content package, video, discussion, and e-assessment. In conclusion, there is a factorial relationship between the system components and learning activities. These components taken together constitute an e-learning experience variable. When the factor loadings between the e-learning experience structure and subcomponents were examined, the discussion interactions in which the learner structured knowledge highlighted. In summary, the discussions, formative assessments, and content activities formed the learners’ e-learning experience together. In order to form a well-structured e-learning environment, these activities together should be experienced by the learners.
Keywords : e learning, learner system interaction, log data, interaction pattern, e learning experience, confirmatory factor analysis