Data Analytics in e-Learning: Approaches and Applications
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Beschreibung
This book focuses on research and development aspects of building data analytics workflows that address various challenges of e-learning applications.
This book represents a guideline for building a data analysis workflow from scratch. Each chapter presents a step of the entire workflow, starting from an available dataset and continuing with building interpretable models, enhancing models, and tackling aspects of evaluating engagement and usability. The related work shows that many papers have focused on machine learning usage and advancement within e-learning systems. However, limited discussions have been found on presenting a detailed complete roadmap from the raw dataset up to the engagement and usability issues. Practical examples and guidelines are provided for designing and implementing new algorithms that address specific problems or functionalities. This roadmap represents a potential resource for various advances of researchers and practitioners in educational datamining and learning analytics.
This book focuses on research and development aspects of building data analytics workflows that address various challenges of e-learning applications.
This book represents a guideline for building a data analysis workflow from scratch. Each chapter presents a step of the entire workflow, starting from an available dataset and continuing with building interpretable models, enhancing models, and tackling aspects of evaluating engagement and usability. The related work shows that many papers have focused on machine learning usage and advancement within e-learning systems. However, limited discussions have been found on presenting a detailed complete roadmap from the raw dataset up to the engagement and usability issues. Practical examples and guidelines are provided for designing and implementing new algorithms that address specific problems or functionalities. This roadmap represents a potential resource for various advances of researchers and practitioners in educational datamining and learning analytics.
Presents in a structured way the experiences of using various machine learning techniques Provides theoretical and practical reference with a rich set of approaches and applications Focuses several successful approaches along with their corresponding developed applications implemented for Tesys
Autor*in
Marian Cristian Mihăescu
Themen in »Data Analytics in e-Learning: Approaches and Applications«
Intelligent Systems Computational Intelligence Data Analytics in e-Learning Machine Learning Data Analysis Workflows Educational Data e-Learning Systems Usability