This book shares original innovations, research, and lessons learned regarding teaching and technological perspectives on trust-based learning systems. Both perspectives are crucial to enhancing the e-Assessment process. In the course of the book, diverse areas of the computer sciences (machine learning, biometric recognition, cloud computing, and learning analytics, amongst others) are addressed. In addition, current trends, privacy, ethical issues, technological solutions, and adaptive educational models are described to provide readers with a global view on the state of the art, the latest challenges, and potential solutions in e-Assessment. As such, the book offers a valuable reference guide for industry, educational institutions, researchers, developers, and practitioners seeking to promote e-Assessment processes.
| Serija: | Lecture Notes on Data Engineering and Communications Technologies |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2019 |
| Knygos puslapių skaičius: | 352 |
| ISBN-10: | 3030293254 |
| ISBN-13: | 9783030293253 |
| Formatas: | Knyga minkštu viršeliu |
| Kalba: | Anglų |
| Žanras: | Artificial intelligence (AI) |
Parašykite atsiliepimą apie „Engineering Data-Driven Adaptive Trust-based e-Assessment Systems: Challenges and Infrastructure Solutions“
