Unveiling the Potential of Learning Analytics in Learning Design: Theoretical Implications for General Education
Volume 43, Issue 2 (2024), pp. 59–71
Pub. online: 11 July 2024
Type: Article
Open Access
Open Access
Published
11 July 2024
11 July 2024
Abstract
The article seeks to explore the possibilities of learning analytics in the improvement of learning design in general education. Hence,
it aims to describe key components of learning analytics and address its advantages and some limitations in education, as well as to
depict the most common learning design models. Theoretical analysis helped to reveal how learning analytics can provide teachers
with valuable insights into student engagement, progress and learning outcomes. By taking into account students’ data on interaction
with course materials, teachers can identify areas for improvement, and make data-informed decisions on pedagogical strategies. The
implications of the article highlight the most common practices on how learning analytics can be used to evaluate the effectiveness of
the learning design, address weaknesses in teaching-learning process, predict course completion rates by identifying student profiles,
etc. The theoretical implications allow for presupposing that the synergy of learning analytics and learning design could serve the
improvement of the quality of general education.