TY - BOOK

T1 - Utilizing learning analytics to support study success

A2 - Ifenthaler, Dirk

A2 - Mah, Dana-Kristin

A2 - Yau, Jane Yin Kim

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019. All Rights reserved.

PY - 2019/1/17

Y1 - 2019/1/17

N2 - Students often enter higher education academically unprepared and with unrealistic perceptions and expectations of university life, which are critical factors that influence students' decisions to leave their institutions prior to degree completion. Advances in educational technology and the current availability of vast amounts of educational data make it possible to represent how students interact with higher education resources, as well as provide insights into students' learning behavior and processes. This volume offers new research in such learning analytics and demonstrates how they support students at institutions of higher education by offering personalized and adaptive support of their learning journey. It focuses on four major areas of discussion: Theoretical perspectives linking learning analytics and study success. Technological innovations for supporting student learning. Issues and challenges for implementing learning analytics at higher education institutions. Case studies showcasing successfully implemented learning analytics strategies at higher education institutions. Utilizing Learning Analytics to Support Study Success ably exemplifies how educational data and innovative digital technologies contribute to successful learning and teaching scenarios and provides critical insight to researchers, graduate students, teachers, and administrators in the general areas of education, educational psychology, academic and organizational development, and instructional technology.

AB - Students often enter higher education academically unprepared and with unrealistic perceptions and expectations of university life, which are critical factors that influence students' decisions to leave their institutions prior to degree completion. Advances in educational technology and the current availability of vast amounts of educational data make it possible to represent how students interact with higher education resources, as well as provide insights into students' learning behavior and processes. This volume offers new research in such learning analytics and demonstrates how they support students at institutions of higher education by offering personalized and adaptive support of their learning journey. It focuses on four major areas of discussion: Theoretical perspectives linking learning analytics and study success. Technological innovations for supporting student learning. Issues and challenges for implementing learning analytics at higher education institutions. Case studies showcasing successfully implemented learning analytics strategies at higher education institutions. Utilizing Learning Analytics to Support Study Success ably exemplifies how educational data and innovative digital technologies contribute to successful learning and teaching scenarios and provides critical insight to researchers, graduate students, teachers, and administrators in the general areas of education, educational psychology, academic and organizational development, and instructional technology.

KW - Educational science

KW - Educational technology

KW - Learning environment

KW - Higher education resources

KW - Learning behavior

KW - Learning analytics

KW - Digital learning environments

KW - Administrative systems

KW - Social platforms

KW - Real-time modelling

KW - Digital technologies

KW - Study success

KW - Higher education institutions

KW - learning and instruction

UR - http://www.scopus.com/inward/record.url?scp=85070303703&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/5cff79a2-5e4b-3d4c-9b56-1b0833a5263c/

U2 - 10.1007/978-3-319-64792-0

DO - 10.1007/978-3-319-64792-0

M3 - Book

AN - SCOPUS:85070303703

SN - 9783319647913

BT - Utilizing learning analytics to support study success

PB - Springer International Publishing AG

ER -