Learning Analytics in Higher Education: A Bibliometric Analysis

The rapid advancement of technology has significantly transformed higher education, leading to an increased focus on learning analytics (LA) emerged as a vital strategy to enhance student outcomes, engagement, and retention rates, amongst many others. This study conducts a bibliometric analysis to investigate publication trends related to the implementation of learning analytics in higher education, examining a total of 235 publications from 1993 to 2024. Utilizing a structured approach, data was collected from the SCOPUS database, followed by statistical analysis and visualization using R Bibliometrix Biblioshiny. The analysis indicates a significant surge in interest since 2016, particularly in related areas of learning analytics, such as artificial intelligence, data analytics, predictive analytics, and self-regulated learning. It is also indicated a strong international collaboration, particularly among authors from Australia, the United Kingdom, and Germany, showing global interest on the topic. The findings reveal key insights into significant publication sources, authorship diversity, co-authorship patterns, indicating a growing trend and importance of international collaboration. Future research is encouraged to explore how AI, emerging technologies, and methodologies impact learning analytics implementation in higher education. This study provides valuable insight into the current state of learning analytics in higher education, highlighting its implication for future research endeavors.