Review of: Ifenthaler, D., Mah, D., & Yau, J.Y. (Eds). (2019). Utilizing analytics to support study success. Cham, Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-319-64792-0

Excerpt

Utilizing Learning Analytics to Support Study Success edited by Dirk Ifenthaler, Dana-Kristin Mah and Jane Yin-Kim Yau illustrates important features of the current state of the art in learning analytics; that despite its nascent, still developing form as a new science of learning, the field shows extensive scope and enormous depth even though it is still young and rapidly growing. By extensiveness, I mean the range from a) finding and acquiring students, b) understanding their motivations and career trajectories, c) offering them current, leading edge knowledge and skills and validating their acquisition and powers of using and acting on what they know and can do, d) delivering them engaging learning experiences at any time, any place, and e) including them into a global network of life-long learners, entrepreneurs and global knowledge workers. By enormity, I mean the semantic distance from a theoretical concept such as ‘systems understanding’ to a technical detail about its potential instantiation in a graph comparison of the kernels (i.e. the discrete probability distributions of the graph’s loop cycles and their f-divergence) present in an expressed mental model map of a student to assess their systems thinking, as in (Giabbanelli, Tawfik and Gupta, Chap. 11). This book dives into the wide and deep potential of learning analytics, with examples, cases, theoretical perspectives and in-depth technical information. …