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

Year 2022, , 1 - 13, 31.01.2022

Sinan Keskin , Halil Yurdugül

https://doi.org/10.31681/jetol.938363

Cited By: 3

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 (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 (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

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