Manage Your Own Learning Analytics


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Manage Your Own Learning Analytics


Manage Your Own Learning Analytics

Author: Elspeth McKay

language: en

Publisher: Springer Nature

Release Date: 2021-12-04


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This book sheds light on the practice of learning analytics, illuminating how others approach their data analysis. At the beginning of the book, a ‘prescriptive 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 analysis); Cognitive Performance Measurement Practices (classical test theory (CTT), Rasch measurement theory (RMT), Item response theory(IRT), Rasch Modeling Tools (research design, setting methodology); and Case Studies (corporate training settings, healthcare industry, and educational courseware design). This book is an important reference for: educational research community and instructional systems designers; corporate training developers; postgraduate course developers; and doctoral students.

Learning Analytics


Learning Analytics

Author: Cristina Hall

language: en

Publisher:

Release Date: 2020


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Utilize organizational data and analytics to make better decisions about managing the learning and development of your workforce.

Learning Analytics: Fundaments, Applications, and Trends


Learning Analytics: Fundaments, Applications, and Trends

Author: Alejandro Peña-Ayala

language: en

Publisher: Springer

Release Date: 2017-02-17


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This book provides a conceptual and empirical perspective on learning analytics, its goal being to disseminate the core concepts, research, and outcomes of this emergent field. Divided into nine chapters, it offers reviews oriented on selected topics, recent advances, and innovative applications. It presents the broad learning analytics landscape and in-depth studies on higher education, adaptive assessment, teaching and learning. In addition, it discusses valuable approaches to coping with personalization and huge data, as well as conceptual topics and specialized applications that have shaped the current state of the art. By identifying fundamentals, highlighting applications, and pointing out current trends, the book offers an essential overview of learning analytics to enhance learning achievement in diverse educational settings. As such, it represents a valuable resource for researchers, practitioners, and students interested in updating their knowledge and finding inspirations for their future work.