Human-Computer Interaction and Knowledge Transfer: Study of E-Learning Achievement

Human-computer interaction influences the effectiveness of e-learning knowledge transfer, so it is necessary to pay attention to user engagement and achievement. The aim of this research is to examine the factors that support e-learning knowledge transfer through achievement and user engagement (self-efficacy, self-confidence, self-esteem). The research method was carried out by surveying e-learning users, namely students, data from students was collected through quantitative questionnaires. The data is then processed using the SmartPLS tool through two tests, namely the PLS Algorithm and Boostrapping. The model was tested using inner and outer tests, and the data was analyzed based on the research hypothesis design. Student interactions with e-learning influence several behaviors that can support e-learning knowledge transfer performance. The research results prove that student e-learning achievement has a positive impact on e-learning knowledge transfer. Several supporting factors play a role in increasing e-learning achievement, namely self-efficacy, self-confidence and self-esteem of students. However, the supporting factors for students are only self-efficacy and self-confidence which are directly able to increase e-learning knowledge transfer. It is known that students who are less able to respect themselves in interacting with e-learning are unable to support knowledge transfer. The rules of human-computer interaction play a role in supporting e-learning knowledge transfer, studies on user behavior need to be considered, especially self-efficacy and self-confidence to support online learning academic performance.