Educational Data Science: Essentials, Approaches, and Tendencies

Educational Data Science: Essentials, Approaches, and Tendencies

Proactive Education based on Empirical Big Data Evidence

Pena-Ayala, Alejandro

Springer Verlag, Singapore

05/2024

291

Mole

9789819900282

15 a 20 dias

Descrição não disponível.
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.
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Educational data science;Knowledge discovery in big data repositories;Educational data mining;Learning analytics;Machine learning