Educational Data Mining and Learning Analytics
Springer International Publishing (Verlag)
978-3-031-41726-9 (ISBN)
- Noch nicht erschienen (ca. Juni 2025)
- Versandkostenfrei innerhalb Deutschlands
- Auch auf Rechnung
- Verfügbarkeit in der Filiale vor Ort prüfen
- Artikel merken
This book is the result of a collaboration between a human editor and an artificial intelligence algorithm to create a machine-generated literature overview of research articles analyzing Educational Data Mining and Learning Analytics. It's a new publication format in which state-of-the-art computer algorithms are applied to select the most relevant articles published in Springer Nature journals and create machine-generated literature reviews by arranging the selected articles in a topical order and creating short summaries of these articles.
The popularity of Educational Data Mining has grown among educators seeking more effective ways to monitor and incentivize student progress and engagement during the COVID-19 pandemic. This has led to increased interest within research communities. The book provides a comprehensive overview of state-of-the-art research in Education Data Mining and its applications. Each chapter includes case studies to support theoretical concepts.The book is of great interest for a wide range of audiences, including computer scientists and educational philosophers.
lt;p>Dr. Tai Tan Mai is currently an Assistant Professor at the School of Computing, Dublin City University, Ireland. He obtained his PhD from the same institution and received prestigious research awards from the Irish Research Council. His research interests include learning analytics, process mining, data mining, and complex systems.
Dr. Marija Bezbradica is an Assistant Professor at the School of Computing, Dublin City University, Ireland. Her research areas include complex systems, predictive and behavioral analytics. She is a co-author of over 40 peer-reviewed scholarly, journal, conference and book articles. She has received international grants from the European Union, SFI/FinTech Fusion, IRC and Enterprise Ireland.
Prof. Martin Crane is a Professor at the School of Computing, Dublin City University, Ireland, a co-author of approximately 75 peer-reviewed scholarly articles. During his 20 years of research, he was PI on funded projects totaling EUR1.5 million and supervised many doctoral and master students to completion. His research areas include learning analytics, quantitative finance and complex systems.
Chapter 1. Introduction.- Chapter 2. Computer-supported collaboration learning.- Chapter 3. Computer-supported self-regulated and personalised learning.- Chapter 4. Computer-supported tutoring.- Chapter 5. Computer-supported learning outcome prediction.- Chapter 6. Smart environment for learning.- Chapter 7. Ethics and Privacy for Learning Analytics.
| Erscheinungsdatum | 11.11.2023 |
|---|---|
| Zusatzinfo | Approx. 245 p. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Schulbuch / Wörterbuch ► Unterrichtsvorbereitung ► Unterrichts-Handreichungen |
| Sozialwissenschaften ► Pädagogik ► Allgemeines / Lexika | |
| Sozialwissenschaften ► Pädagogik ► Erwachsenenbildung | |
| Schlagworte | Academic Decision Support System • Academic Resilience • Computer-supported learning systems • Data Mining • Development of Methods • EDM/LA • educational data mining • Educational Research • Incentivize student progress • Learning Analytics • learning behaviors • Learning Processes • Learning research • Machine-Generated Literature Overview • Monitor student progress • Student Engagement • Student learning behaviors • Third educational path |
| ISBN-10 | 3-031-41726-7 / 3031417267 |
| ISBN-13 | 978-3-031-41726-9 / 9783031417269 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
