Intelligent Data Analysis for e‎-Learning‎:‎ Enhancing Security and Trustworthiness in Online Learning Systems addresses information security within e‎-Learning based on trustworthiness assessment and prediction‎.‎ Over the past decade‎,‎ many learning management systems have appeared in the education market‎.‎ Security in these systems is essential for protecting against unfair and dishonest conduct‎-most notably cheating‎-however‎,‎ e‎-Learning services are often designed and implemented without considering security requirements‎.‎ This book provides functional approaches of trustworthiness analysis‎,‎ modeling‎,‎ assessment‎,‎ and prediction for stronger security and support in online learning‎,‎ highlighting the security deficiencies found in most online collaborative learning systems‎.‎ The book explores trustworthiness methodologies based on collective intelligence than can overcome these deficiencies‎.‎ It examines trustworthiness analysis that utilizes the large amounts of data‎-learning activities generate‎.‎ In addition‎,‎ as processing this data is costly‎,‎ the book offers a parallel processing paradigm that can support learning activities in real‎-time‎.‎ The book discusses data visualization methods for managing e‎-Learning‎,‎ providing the tools needed to analyze the data collected‎.‎ Using a case‎-based approach‎,‎ the book concludes with models and methodologies for evaluating and validating security in e‎-Learning systems‎.‎ Indexing‎:‎ The books of this series are submitted to EI‎-Compendex and SCOPUS

• Author‎:‎ Jorge Miguel‎,‎ Santi Caballe
• Publisher‎:‎ Academic Press
• ISBN‎:‎ 9780128045350