Abstract
Current study on e-Learning user’s behaviour model obtained the specific models. In many cases, the e-Learning user’s behaviour model for open source e-Learning system such as Moodle, which can predict learning outcome or learning performance is still defi cient and cannot generally apply in many institutions due to the fact that the majority of prediction models were developed particularly for certain institutions. This study proposes to produce a general model that can make a prediction of learning outcome inspired by Skinner’s theory, which explains the relationship between learner, achievement, and learner reinforcement. This study proposes similar patterns in e-Learning user’s behaviour models of different institutions by the data-mining technique based on the learning environment theory. Therefore, this research is conducted in three main phases; include data preparation from weblog of different institutions with the same e-Learning system, data extraction by the accurate classifi er model fi nding process and model verification for generating a verification pattern. The research outcome will be a similar pattern that could be used as a direction for creating a more appropriate e-Learning users’ behaviour model and could be used broadly in other higher institutions.
Highlights
In many academic institutions as well as commercial organizations, the system that can support and improve learning within an organization and institution nowadays is continuously developing, the Learning ManagementSystem (LMS) nowadays plays more crucial roles in distance learning because of its manageability
Previous learning models constructed by e-Learning web-log have explained their relevant determinants
These models aim to predict the learner status for learning direction change until learners find their best learning advantage. This concept is one solution to clear the doubt of how learners achieve high learning outcomes
Summary
System (LMS) nowadays plays more crucial roles in distance learning because of its manageability. This system is notably able to manage the registered users, manage course catalogues, record data from learners and is equipped with reports for the system management. For distance-learning education, the LMS software is very economical and practicable. Besides that, this software can be used in many different phases that can support users in terms of performing content preparation by keeping the users’ records. The web log is a hidden useful part, which is a helpful factor for developing a stable and appropriate e-Learning users’ behaviour model by using the data-mining technique. There are several works that attempt to improve and develop the novelty in various features for its new version which can be catagorized into two aspects as e-Learning tools and e-Learning users’ behaviour models (Figure 1)
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