Adoption of Data Analytics in Higher Education Learning and Teaching

• In Event: Book Sharing (A-S)

Short Description

The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms.

Within this presentation, the book series "Advances in Analytics for Learning and Teaching" is presented, including opportunities for publishing monographs and edited volumes (https://www.springer.com/series/16338).

Author

• Presenter: Dirk Ifenthaler, University of Mannheim