This book provides a conceptual and empirical perspective on learning analytics, its goal being to disseminate the core concepts, research, and outcomes of this emergent field. Divided into nine chapters, it offers reviews oriented on selected topics, recent advances, and innovative applications. It presents the broad learning analytics landscape and in-depth studies on higher education, adaptive assessment, teaching and learning. In addition, it discusses valuable approaches to coping with personalization and huge data, as well as conceptual topics and specialized applications that have shaped the current state of the art.
By identifying fundamentals, highlighting applications, and pointing out current trends, the book offers an essential overview of learning analytics to enhance learning achievement in diverse educational settings. As such, it represents a valuable resource for researchers, practitioners, and students interested in updating their knowledge and finding inspirations for their future work.
Table of Contents
Learning Analytics in Higher Education.- A Literature Review.- Teaching and Learning Analytics to support Teacher Inquiry: A Systematic Literature Review.- A Landscape of Learning Analytics: An Exercise to Highlight the Nature of an Emergent Field.- A Review of Recent Advances in Adaptive Assessment.- Data-driven Personalization of Student Learning Support in Higher Education.- Overcoming the MOOC data deluge with learning analytic dashboards.- A Priori Knowledge in Learning Analytics.- Knowledge Discovery from the Programme for International Student Assessment.- A Learning Analytics Approach for Job Scheduling on Cloud Servers