Analysing Users' Interactions with Khan Academy Repositories

Yassine, Sahar; Kadry, Seifedine; Sicilia, Miguel-Ángel

ISBN 10: 3030891658 / ISBN 13: 9783030891657

Verlag: Springer, 2021

Beschreibung

Print on Demand.

Bestandsnummer des Verkäufers 401802927

Bibliografische Details

• Titel: Analysing Users' Interactions with Khan Academy Repositories
• Verlag: Springer
• Erscheinungsjahr: 2021
• Sprache: Englisch
• ISBN-10: 3030891658
• ISBN-13: 9783030891657
• Einband: Hardcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

1. Introduction to Online Learning Repositories.- 2. Research Objectives.- 3. Literature Review.- 4. Methodology.- 5. Data acquisition.- 6. Assessing Online Learning Repository with Descriptive Statistical Analysis.- 7. Detecting Communities in Online Learning Repository.- 8. SNA Measures and Users' Interactions.- 9. Conclusions.- 10. Future work.

Über die Autorin bzw. den Autor

Sahar Yassine has a PhD in Computer Science from Alcalá University, Spain. Her Doctoral research investigates interactions with online learning and focuses on detecting communities in e‐learning environments. She has interests in educational repositories, learning‐technology and social network analysis techniques.

Seifedine Kadry has a bachelor’s degree in applied mathematics in 1999 from Lebanese University, MS degree in Computation in 2002 from Reims University (France) and EPFL (Lausanne), PhD in 2007 from Blaise Pascal University (France), HDR degree in Engineering Science in 2017 from Rouen University. At present his research focuses on education using technology, smart cities, system prognostics, stochastic systems, and probability and reliability analysis. He is a fellow of IET, fellow of ACSIT and ABET program evaluator. He is a full professor of data science at Noroff University College, Kristiansand, Norway.

Miguel‐Ángel Sicilia is currently full professor at the Computer Science Department of the University of Alcalá (Madrid, Spain). He holds degrees in Computer Science (Pontifical University of Salamanca) and in Information Science (University of Alcalá) and a PhD in Computer Science from Carlos III University. Before joining academia, Miguel Angel was part of the R&D and e‐commerce architecture staff of iSOCO. Miguel Angel has developed his research activity in the fields of Artificial Intelligence, machine learning and analytics applied to different fields, including learning, health, computational science, command and control systems and information security.