Educational Data Science: Essentials, Approaches, and Tendencies
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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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
Educational data science;Knowledge discovery in big data repositories;Educational data mining;Learning analytics;Machine learning
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.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
