Abstract
This chapter highlights the significance of learning analytics (LA) in educational settings. A growing number of studies have been conducted in lieu of LA. LA is a notion that has emerged as a technique of exploiting the massive amount of learner data created by electronic system operations for educational purposes. As a recent learner-cantered method that strives to understand and optimize learning and learning environments, LA holds some pivotal benefits to enhance the teaching-learning process and makes a significant contribution to the field of educational design by analysing, storing, and processing the relevant data and provides an evidence-based decision-making process for all stakeholders ranging from institutions to researchers. The chapter then moves toward the theoretical framework on LA by exploring and understanding of the nature of learning and improve educational environments. In the final part, the significance of LA in educational settings and higher institutions is presented.
TopThe Significance Of Learning Analytics In Educational Settings
An approach to decision-making and understanding student learning that is informed by data has evolved as an effective instrument in educational settings (Banihashem et al., 2018). In this vein, LA has emerged as a valuable tool in educational settings and has been used by educational institutions more and more to detect and support students who may suffer from low performance or disorder (Oliva-Córdova, 2021). According to Banihashem et al. (2018), the capacity to comprehend how students learn is one of the potential benefits of LA. Another potential benefit is the move from speculative decision-making toward practices that are based on evidence. This can be actualized by the substantial use of digital resources for self-directed learning, which is within the scope of LA based-on data from student questionnaires (Scott et al., 2017). Thus, LA has the potential to yield significant advantages in education, including enhanced service quality, enhanced student engagement, enhanced learning outcomes, accessibility to immediate feedback, and personalization of learning experiences (Mian et al., 2022). In addition, LA is dependent on a tailored approach for both teachers and students, which highlights its ability to cater to the specific learning requirements of individuals (Maseleno et al., 2018).
Key Terms in this Chapter
Content Management System (CMS): It serves as an application to help users create, edit, publish, and store digital content through a software system.
Learning Analytics (LA): It is the process of measuring, collecting, analyzing, and reporting data about learners and educational contexts.
Learning Management System (LMS): It provide virtual classroom environments that support the learning process.