A scoping review of empirical studies on theory-driven learning analytics. Issue 1 (2nd January 2022) - Wang, Qin; Mousavi, Amin; Lu, Chang
Abstract: The field of learning analytics (LA) is developing rapidly. However, previous empirical studies on LA were largely data-driven. Little attention has been paid to theory-driven LA studies. The present scoping review identified and summarized empirical theory-driven LA studies, aiming to reveal how theories were integrated into LA. The review examined 37 peer-reviewed journal articles published from 2016 to 2020 from six databases. Results show that most studies were guided by the theories of self-regulated learning and social constructivism; most integrated theories into LA for better interpreting the data analysis results; and most linked theoretical constructs and log variables directly. Several studies employed well-developed survey instruments to measure theoretical constructs. The review results indicate that LA studies still need to strive for new theory advances in learning. Recommendations for future study are discussed.