Caballé S., Conesa J. (Eds.) Software Data Engineering for Network eLearning Environments: Analytics and Awareness Learning Services

Springer International Publishing AG, 2018. — 237 p. — (Lecture Notes on Data Engineering and Communications Technologies 11) — ISBN: 3319683179.This book presents original research on analytics and context awareness with regard to providing sophisticated learning services for all stakeholders in the eLearning context. It offers essential information on the definition, modeling, development and deployment of services for these stakeholders.
Data analysis has long-since been a cornerstone of eLearning, supplying learners, teachers, researchers, managers and policymakers with valuable information on learning activities and design. With the rapid development of Internet technologies and sophisticated online learning environments, increasing volumes and varieties of data are being generated, and data analysis has moved on to more complex analysis techniques, such as educational data mining and learning analytics. Now powered by cloud technologies, online learning environments are capable of gathering and storing massive amounts of data in various formats, of tracking user-system and user-user interactions, and of delivering rich contextual information.Predictive Analytics: Another Vision of the Learning Process
A Procedural Learning and Institutional Analytics Framework
Engagement Analytics: A Microlevel Approach to Measure and Visualize Student Engagement
Learning Analytics in Mobile Applications Based on Multimodal Interaction
Increasing the Role of Data Analytics in m-Learning Conversational Applications
Enhancing Virtual Learning Spaces: The Impact of the Gaming Analytics
Advice for Action with Automatic Feedback Systems
Towards Full Engagement for Open Online Education. A Practical Experience from MicroMasters at edX
A Data Mining Approach to Identify the Factors Affecting the Academic Success of Tertiary Students in Sri Lanka
Evaluating the Acceptance of e-Learning Systems via Subjective and Objective Data Analysis