Educational Data Science: Essentials, Approaches, and Tendencies Proactive Education based on Empirical Big Data Evidence /
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,...
Wedi'i Gadw mewn:
| Awdur Corfforaethol: | |
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| Awduron Eraill: | |
| Fformat: | Electronig eLyfr |
| Iaith: | Saesneg |
| Cyhoeddwyd: |
Singapore :
Springer Nature Singapore : Imprint: Springer,
2023.
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| Rhifyn: | 1st ed. 2023. |
| Cyfres: | Big Data Management,
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| Pynciau: | |
| Mynediad Ar-lein: | https://doi.org/10.1007/978-981-99-0026-8 |
| Tagiau: |
Ychwanegu Tag
Dim Tagiau, Byddwch y cyntaf i dagio'r cofnod hwn!
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Tabl Cynhwysion:
- 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.