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Titlebook: Big Data and Learning Analytics in Higher Education; Current Theory and P Ben Kei Daniel Book 2017 Springer International Publishing Switze

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樓主: retort
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發(fā)表于 2025-3-28 17:52:57 | 只看該作者
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發(fā)表于 2025-3-28 21:58:43 | 只看該作者
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發(fā)表于 2025-3-29 00:26:41 | 只看該作者
Curricular and Learning Analytics: A Big Data Perspectiveing concerns, and nurturing of cognitive aspects of learners, among others. Learning Analytics systems can engage learners to detect and appreciate insights generated by others, engage learners to investigate models on learning factors, and engage learners to create new insights. This chapter offers
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發(fā)表于 2025-3-29 03:24:50 | 只看該作者
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發(fā)表于 2025-3-29 07:43:41 | 只看該作者
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發(fā)表于 2025-3-29 14:05:22 | 只看該作者
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發(fā)表于 2025-3-29 15:47:41 | 只看該作者
Predicting Four-Year Student Success from Two-Year Student Datat focused on a series of academic milestones that students must achieve prior to earning a 4-year credential. Those milestones include the first-term GPA, re-enrollment, and program completion. The purpose of this project was to develop an integrated database that contains key data on student demogr
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發(fā)表于 2025-3-29 21:51:32 | 只看該作者
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發(fā)表于 2025-3-30 02:50:50 | 只看該作者
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發(fā)表于 2025-3-30 07:38:50 | 只看該作者
Thoughts on Recent Trends and Future Research Perspectives in Big Data and Analytics in Higher Educaove decision-making, analytics and intuition-based decision-making should be key components in this “Big Data” era. Educational data mining and learning analytics are becoming the lingua franca for those institutions who seek to improve their strategic and operational decision-making abilities. This chapter highlights some thoughts in these areas.
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