Software Data Engineering for Network eLearning Environments (eBook, PDF)

Analytics and Awareness Learning Services
Redaktion: Caballé, Santi; Conesa, Jordi

• Format: PDF

Produktbeschreibung

Explores the state of the art in software tools and innovative learning strategies for providing effective and efficient solutions to the various problems and challenges currently facing eLearning from a software data engineering perspective

Highlights stimulating practical research from leading international experts

Provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 228
• Erscheinungstermin: 9. Februar 2018
• Englisch
• ISBN-13: 9783319683188
• Artikelnr.: 52941107

Inhaltsangabe

SECTION I: Strategies and Methodologies based on Learning Data Analysis.-Chapter 1. Predictive Analytics: Another Vision of the Learning Process.-Chapter 2. A Procedural Learning and Institutional Analytics Framework.-Chapter 3. Extending learning analytics with microlevel student engagement data.-Chapter 4. Learning analytics in mobile applications based on multimodal interaction.-SECTION II: Applications of Analytics and Awareness Learning Services to eLearning.-Chapter 5. The role of data analytics in m-learning conversational applications.-Chapter 6. Enhancing Virtual Learning Spaces: the impact of the Gaming Analytics.-Chapter 7. Advice for Action with Automatic Feedback System s.-SECTION III: Practical Use Cases and Evaluation in Real Context of eLearning.-Chapter 8. Towards Full Engagement for Open Online Education. A practical experience from MicroMasters at edX.-Chapter 9. A Data Mining Approach to Identify the Factors Affec ting to the Academic Success of Tertiary Students inSri Lanka.-Chapter 10. Evaluating the acceptance of e-learning systems via subjective and objective data analysis.