A LAK of Direction: Misalignment Between the Goals of Learning Analytics and its Research Scholarship
crossref(2022)
Abstract
Learning analytics defines itself with a focus on learner data, with corresponding goals of understanding and optimizing student learning. In this regard, learning analytics research, ideally, should be characterized by studies that make use of data from learners engaged in education systems, should measure student learning, and should make efforts to intervene and improve these learning environments. However, a common concern among members of the learning analytics research community is that these standards are not being met. In the current study, we review a large and comprehensive sample of research articles from the proceedings of two recent Learning Analytics and Knowledge conferences, the premier conference venue for learning analytics research. We find that 36.3% of articles do not analyze data from learners in a formal education system, 70.5% do not include any measure of learning, and 91.4% of articles do not attempt to intervene in the learning environment. We contrast these findings with the stated definition of learning analytics, and infer, like others, that scholarship in learning analytics research presently lacks clear direction toward its stated goals.
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