東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Adoption of data analytics in higher...

Ifenthaler, Dirk.

Linked to FindBook

Google Book

Amazon

博客來

Adoption of data analytics in higher education learning and teaching

Record Type:	Electronic resources : Monograph/item
Title/Author:	Adoption of data analytics in higher education learning and teaching/ edited by Dirk Ifenthaler, David Gibson.
other author:	Ifenthaler, Dirk.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xxxviii, 434 p. :ill., digital ;24 cm.
[NT 15003449]:	Part I. Theoretical Foundations and Frameworks -- Part II. Technological Infrastructure and Staff Requirements -- Part III. Institutional Governance and Policy Implementation -- Part IV. Case Studies.
Contained By:	Springer Nature eBook
Subject:	Education, Higher - Research - United States -
Online resource:	https://doi.org/10.1007/978-3-030-47392-1
ISBN:	9783030473921

Adoption of data analytics in higher education learning and teaching
Adoption of data analytics in higher education learning and teaching[electronic resource] /edited by Dirk Ifenthaler, David Gibson. - Cham :Springer International Publishing :2020. - xxxviii, 434 p. :ill., digital ;24 cm. - Advances in analytics for learning and teaching,2662-2122. - Advances in analytics for learning and teaching..

Part I. Theoretical Foundations and Frameworks -- Part II. Technological Infrastructure and Staff Requirements -- Part III. Institutional Governance and Policy Implementation -- Part IV. Case Studies.

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. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.

ISBN: 9783030473921

Standard No.: 10.1007/978-3-030-47392-1doiSubjects--Topical Terms:

3525689
Education, Higher
--Research--United States

LC Class. No.: LB2395.7 / .A46 2020

Dewey Class. No.: 378.007

Adoption of data analytics in higher education learning and teaching
LDR:02680nmm a2200337 a 4500 001 2255866
003 DE-He213
005 20201224134855.0
006 m d
007 cr nn 008maaau
008 220420s2020 sz s 0 eng d
020 $a 9783030473921 $q (electronic bk.)
020 $a 9783030473914 $q (paper)
024 7 $a 10.1007/978-3-030-47392-1 $2 doi
035 $a 978-3-030-47392-1
040 $a GP $c GP
041 0 $a eng
050 4 $a LB2395.7 $b .A46 2020
072 7 $a JNV $2 bicssc
072 7 $a EDU039000 $2 bisacsh
072 7 $a JNV $2 thema
082 0 4 $a 378.007 $2 23
090 $a LB2395.7 $b .A239 2020
245 0 0 $a Adoption of data analytics in higher education learning and teaching $h [electronic resource] / $c edited by Dirk Ifenthaler, David Gibson.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xxxviii, 434 p. : $b ill., digital ; $c 24 cm.
490 1 $a Advances in analytics for learning and teaching, $x 2662-2122
505 0 $a Part I. Theoretical Foundations and Frameworks -- Part II. Technological Infrastructure and Staff Requirements -- Part III. Institutional Governance and Policy Implementation -- Part IV. Case Studies.
520 $a 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. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.
650 0 $a Education, Higher $x Research $z United States $x Data processing. $3 3525689
650 0 $a Education, Higher $x Research $z United States $x Statistical methods. $3 3525690
650 0 $a Educational statistics. $3 520601
650 1 4 $a Educational Technology. $3 876844
650 2 4 $a Learning & Instruction. $3 893930
650 2 4 $a Higher Education. $3 898504
700 1 $a Ifenthaler, Dirk. $3 901275
700 1 $a Gibson, David. $3 850468
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Advances in analytics for learning and teaching. $3 3451185
856 4 0 $u https://doi.org/10.1007/978-3-030-47392-1
950 $a Education (SpringerNature-41171)