Learning Analytics in Higher Education: A Decade in Systematic Literature Review

Abstract

In the last decade, learning analytics (LA) has evolved in a positive way, considering that the term emerged in 2011 through the society for learning analytics research (SoLAR). This area of data analytics can be identified as a specialization of educational data mining (EDM). LA emphasizes student learning outcomes. In addition to, a better understanding of student learning behavior and processes. While EDM focuses on helping teachers and students with the analysis of the learning process using popular data mining methods. The purpose of this research is to explore the first decade of work with the application of learning analytics in higher education institutions (HEI) in the context of tutoring information systems (TIS), with the intention of supporting institutions, teachers and students to decrease dropout rates. This article presents a systematic literature review (SLR) with 17 primary studies, comprised between 2014 and 2024. The findings reflect the use of LA in improving or optimizing learning using student academic history obtained through learning management systems (LMS), noting the scarcity of works with a focus on tutoring or academic advising. Ultimately, a gap is opened to apply LA in HEI, with information from institutional tutoring program (PIT), integrated with information from an LMS, to contribute to student permanence.