Titlebook: Manage Your Own Learning Analytics; Implement a Rasch Mo Elspeth McKay Book 2022 Springer Nature Switzerland AG 2022 Cognitive Performance

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書目名稱Manage Your Own Learning Analytics影響因子(影響力)




書目名稱Manage Your Own Learning Analytics影響因子(影響力)學科排名




書目名稱Manage Your Own Learning Analytics網(wǎng)絡公開度




書目名稱Manage Your Own Learning Analytics網(wǎng)絡公開度學科排名




書目名稱Manage Your Own Learning Analytics被引頻次




書目名稱Manage Your Own Learning Analytics被引頻次學科排名




書目名稱Manage Your Own Learning Analytics年度引用




書目名稱Manage Your Own Learning Analytics年度引用學科排名




書目名稱Manage Your Own Learning Analytics讀者反饋




書目名稱Manage Your Own Learning Analytics讀者反饋學科排名

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https://doi.org/10.1007/978-3-030-86316-6Cognitive Performance Measurement; Learning Analytics; Instructional Design; Instructional Systems Desi

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978-3-030-86318-0Springer Nature Switzerland AG 2022

騷擾

Manage Your Own Learning Analytics978-3-030-86316-6Series ISSN 2190-3018 Series E-ISSN 2190-3026

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Book 2022escriptive learning analytics planning model’ gives straightforward instructions for people to follow. This book is organized into ten chapters, falling into four topical sections: Managing Learning Analytics (overview, instructional systems design (ISD), instructional design, and planning data anal

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Using Log Stream Data and Item Response Theory to Understand Proficiency in Collaboration,ss stream data of collaboration into formative assessment data that can be analysed using Item Response Theory. The application of this model in turn allows the interpretation of the data as levels of proficiency that we can use to map or monitor progress in collaborative skills.

Alveoli

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Industry 4.0: Learning Analytics Using Artificial Intelligence and Advanced Industry Applications,em to show the different use of AI. This book chapter explains: the meaning of the learning analytics in Industry 4.0 and education and its affiliated areas; AI and its related areas with examples from state-of-the-art corporate applications and solutions based on AI technologies integrated into the learning analytics.

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Machine Learning for Learning Analytics for Meta-cognitive Support,in the student’s mind. The sources for the chosen direction rest upon earlier research into media-support for conceptual learning. This chapter may elicit the discussion on how far technology-driven innovations can bypass the existing repertoire of earlier didactic solutions.