Go to main content

Educational data science : essentials, approaches, and tendencies : proactive education based on empirical big data evidence / Alejandro Peña-Ayala, editor.

Peña-Ayala, Alejandro, editor.
2023
LB1028.43
Available Online
Formats
Format
BibTeX
MARCXML
TextMARC
MARC
DublinCore
EndNote
NLM
RefWorks
RIS
Add to Basket
Cite
Citation

Linked e-resources

Linked Resource
Online Access
Concurrent users
Unlimited
Authorized users
Authorized users
Document Delivery Supplied
Can lend chapters, not whole ebooks

Details

Title
Educational data science : essentials, approaches, and tendencies : proactive education based on empirical big data evidence / Alejandro Peña-Ayala, editor.
ISBN
9789819900268 (electronic bk.)
9819900263 (electronic bk.)
9789819900251
9819900255
DOI
https://doi.org/10.1007/978-981-99-0026-8
Published
Singapore : Springer, 2023.
Language
English
Description
1 online resource (383 pages) : illustrations (black and white, and color).
Item Number
10.1007/978-981-99-0026-8 doi
Call Number
LB1028.43
Dewey Decimal Classification
370.28557
Summary
This book describes theoretical elements, practical approaches, and specialized tools that systematically organize, characterize, and analyze big data gathered from educational affairs and settings. Moreover, the book shows several inference criteria to leverage and produce descriptive, explanatory, and predictive closures to study and understand education phenomena at in classroom and online environments. This is why diverse researchers and scholars contribute with valuable chapters to ground with well-sounded theoretical and methodological constructs in the novel field of Educational Data Science (EDS), which examines academic big data repositories, as well as to introduces systematic reviews, reveals valuable insights, and promotes its application to extend its practice. EDS as a transdisciplinary field relies on statistics, probability, machine learning, data mining, and analytics, in addition to biological, psychological, and neurological knowledge about learning science. With this in mind, the book is devoted to those that are in charge of educational management, educators, pedagogues, academics, computer technologists, researchers, and postgraduate students, who pursue to acquire a conceptual, formal, and practical landscape of how to deploy EDS to build proactive, real- time, and reactive applications that personalize education, enhance teaching, and improve learning!
Note
Includes index.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Peña-Ayala, Alejandro, editor.
Series
Big data management.
Available in Other Form
Educational data science - essentials, approaches, and tendencies.
Linked Resources
Online Access
Record Appears in
Online Resources > Ebooks
All Resources
1. Engaging in Student-Centered Educational Data Science through Learning Engineering
2. A review of clustering models in educational data science towards fairness-aware learning
3. Educational Data Science: Is an Umbrella Term or an Emergent Domain?
4. Educational Data Science Approach for End-to-End Quality Assurance Process for Building Credit-Worthy Online Courses
5. Understanding the Effect of Cohesion in Academic Writing Clarity Using Education Data Science
6. Sequential pattern mining in educational data: the application context, potential, strengths, and limitations
7. Sync Ratio and Cluster Heat Map for Visualizing Student Engagement.

Browse Subjects

Show more subjects...

Statistics

from
to
Export