Speaker
Description
In the context of digital transformation, instructors’ digital competence has become a crucial factor affecting teaching quality and students’ learning experience. Digital competence is not simply a capability of using technology, but it also includes integrating digital tools to design lessons, evaluate, provide feedback, and support learning effectively. However, feedback practice and personalized learning are still a research gap, especially in university education; both lecturers and students need to adapt to digital technology. The study aims to discover the effect of digital competence on students’ feedback and personalized learning. The quantitative approach with a cross-sectional survey design is mainly applied to this study, including observation, document analysis, and a questionnaire. Data collection is done through the questionnaire, measuring three main variables: instructors’ digital competence, feedback quality, and personalized learning level. Especially, the data analysis is based on the SEM model (SmartPLS4) to test research hypotheses and evaluate the relationship among variables. The expected results show the positive effect of digital competence on feedback effectiveness and personalized learning. Instructors with good capabilities of using technology can integrate digital tools to provide in-time feedback, transparency, and flexibility to meet learning needs. Effective feedback, which can strongly promote autonomous learning by supporting students with self-regulated strategies, is the intermediary element between digital competence and personalized learning. The study significantly contributes to developing professional training programs for instructors, establishing a theoretical foundation of digital competence, creating a flexible learning environment with a student-centered approach, and providing positive feedback to meet students’ learning needs effectively.
