東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Big data in education = pedagogy and...

Prodromou, Theodosia.

FindBook

Google Book

Amazon

博客來

Big data in education = pedagogy and research /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Big data in education/ edited by Theodosia Prodromou.
其他題名:	pedagogy and research /
其他作者:	Prodromou, Theodosia.
出版者:	Cham :Springer International Publishing : : 2021.,
面頁冊數:	xii, 247 p. :ill. (some col.), digital ;24 cm.
內容註:	Part 1: Theoretical and ethical concerns -- 1 Big Data in academic research--Challenges, pitfalls, and opportunities -- Part 2: Teaching people to use Big Data effectively -- 2 Big Data for Early Learners -- 3 Using Big Data in a Master of Applied Statistics unit -- 4 Statistical education as part of the digital transformation of statistical offices -- Part 3: Using Big Data to improve teaching -- 5 Big data, analytics and education: Challenges, opportunities and an example from a large university unit -- 6 Enhancing learning outcomes with 'big data' from pedagogy for conceptual thinking with meaning equivalence reusable learning objects (MERLO) and interactive concept discovery (INCOD) -- 7 Employing Authentic Analytics for More Authentic Tasks -- 8 Learning from Learning Analytics: How much do we know about patterns of student engagement? -- Part 4: Educational systems that use Big Data -- 9 Museum Big Data: Perceptions and practices -- 10 Analysing aspects of Brazilian curricula for teaching statistics involving Big Data -- Part 5: Concluding Comments.
Contained By:	Springer Nature eBook
標題:	Education - Research -
電子資源:	https://doi.org/10.1007/978-3-030-76841-6
ISBN:	9783030768416

Big data in education = pedagogy and research /
Big data in educationpedagogy and research /[electronic resource] :edited by Theodosia Prodromou. - Cham :Springer International Publishing :2021. - xii, 247 p. :ill. (some col.), digital ;24 cm. - Policy implications of research in education,v. 132543-0297 ;. - Policy implications of research in education ;v. 13..

Part 1: Theoretical and ethical concerns -- 1 Big Data in academic research--Challenges, pitfalls, and opportunities -- Part 2: Teaching people to use Big Data effectively -- 2 Big Data for Early Learners -- 3 Using Big Data in a Master of Applied Statistics unit -- 4 Statistical education as part of the digital transformation of statistical offices -- Part 3: Using Big Data to improve teaching -- 5 Big data, analytics and education: Challenges, opportunities and an example from a large university unit -- 6 Enhancing learning outcomes with 'big data' from pedagogy for conceptual thinking with meaning equivalence reusable learning objects (MERLO) and interactive concept discovery (INCOD) -- 7 Employing Authentic Analytics for More Authentic Tasks -- 8 Learning from Learning Analytics: How much do we know about patterns of student engagement? -- Part 4: Educational systems that use Big Data -- 9 Museum Big Data: Perceptions and practices -- 10 Analysing aspects of Brazilian curricula for teaching statistics involving Big Data -- Part 5: Concluding Comments.

This book discusses how Big Data could be implemented in educational settings and research, using empirical data and suggesting both best practices and areas in which to invest future research and development. It also explores: 1) the use of learning analytics to improve learning and teaching; 2) the opportunities and challenges of learning analytics in education. As Big Data becomes a common part of the fabric of our world, education and research are challenged to use this data to improve educational and research systems, and also are tasked with teaching coming generations to deal with Big Data both effectively and ethically. The Big Data era is changing the data landscape for statistical analysis, the ways in which data is captured and presented, and the necessary level of statistical literacy to analyse and interpret data for future decision making. The advent of Big Data accentuates the need to enable citizens to develop statistical skills, thinking and reasoning needed for representing, integrating and exploring complex information. This book offers guidance to researchers who are seeking suitable topics to explore. It presents research into the skills needed by data practitioners (data analysts, data managers, statisticians, and data consumers, academics), and provides insights into the statistical skills, thinking and reasoning needed by educators and researchers in the future to work with Big Data. This book serves as a concise reference for policymakers, who must make critical decisions regarding funding and applications.

ISBN: 9783030768416

Standard No.: 10.1007/978-3-030-76841-6doiSubjects--Topical Terms:

3522005
Education
--Research

LC Class. No.: LB1028.43 / .B54 2021

Dewey Class. No.: 371.334

Big data in education = pedagogy and research /
LDR:03695nmm a2200337 a 4500 001 2253638
003 DE-He213
005 20211004192152.0
006 m d
007 cr nn 008maaau
008 220327s2021 sz s 0 eng d
020 $a 9783030768416 $q (electronic bk.)
020 $a 9783030768409 $q (paper)
024 7 $a 10.1007/978-3-030-76841-6 $2 doi
035 $a 978-3-030-76841-6
040 $a GP $c GP
041 0 $a eng
050 4 $a LB1028.43 $b .B54 2021
072 7 $a JN $2 bicssc
072 7 $a EDU000000 $2 bisacsh
072 7 $a JN $2 thema
082 0 4 $a 371.334 $2 23
090 $a LB1028.43 $b .B592 2021
245 0 0 $a Big data in education $h [electronic resource] : $b pedagogy and research / $c edited by Theodosia Prodromou.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xii, 247 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Policy implications of research in education, $x 2543-0297 ; $v v. 13
505 0 $a Part 1: Theoretical and ethical concerns -- 1 Big Data in academic research--Challenges, pitfalls, and opportunities -- Part 2: Teaching people to use Big Data effectively -- 2 Big Data for Early Learners -- 3 Using Big Data in a Master of Applied Statistics unit -- 4 Statistical education as part of the digital transformation of statistical offices -- Part 3: Using Big Data to improve teaching -- 5 Big data, analytics and education: Challenges, opportunities and an example from a large university unit -- 6 Enhancing learning outcomes with 'big data' from pedagogy for conceptual thinking with meaning equivalence reusable learning objects (MERLO) and interactive concept discovery (INCOD) -- 7 Employing Authentic Analytics for More Authentic Tasks -- 8 Learning from Learning Analytics: How much do we know about patterns of student engagement? -- Part 4: Educational systems that use Big Data -- 9 Museum Big Data: Perceptions and practices -- 10 Analysing aspects of Brazilian curricula for teaching statistics involving Big Data -- Part 5: Concluding Comments.
520 $a This book discusses how Big Data could be implemented in educational settings and research, using empirical data and suggesting both best practices and areas in which to invest future research and development. It also explores: 1) the use of learning analytics to improve learning and teaching; 2) the opportunities and challenges of learning analytics in education. As Big Data becomes a common part of the fabric of our world, education and research are challenged to use this data to improve educational and research systems, and also are tasked with teaching coming generations to deal with Big Data both effectively and ethically. The Big Data era is changing the data landscape for statistical analysis, the ways in which data is captured and presented, and the necessary level of statistical literacy to analyse and interpret data for future decision making. The advent of Big Data accentuates the need to enable citizens to develop statistical skills, thinking and reasoning needed for representing, integrating and exploring complex information. This book offers guidance to researchers who are seeking suitable topics to explore. It presents research into the skills needed by data practitioners (data analysts, data managers, statisticians, and data consumers, academics), and provides insights into the statistical skills, thinking and reasoning needed by educators and researchers in the future to work with Big Data. This book serves as a concise reference for policymakers, who must make critical decisions regarding funding and applications.
650 0 $a Education $x Research $x Data processing. $3 3522005
650 0 $a Big data. $3 2045508
650 1 4 $a Education, general. $3 2162157
650 2 4 $a Curriculum Studies. $3 895988
650 2 4 $a Higher Education. $3 898504
700 1 $a Prodromou, Theodosia. $3 3522003
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Policy implications of research in education ; $v v. 13. $3 3522004
856 4 0 $u https://doi.org/10.1007/978-3-030-76841-6
950 $a Education (SpringerNature-41171)