Pricelists.org Pricelists.org Iniciar sesión Registrarse

AI Injected e-Learning

☆☆☆☆☆ (0 reviews)
Show price history
AI Injected e-Learning
Lowest price (incl. delivery)
21 449,00 JPY
Typical price2 918,85 PLN
Lowest (90 days)117,69 PLN
Offers6
Last updatedhace 1 semana
See best offer
Price history (90 days)
Full history
2026-08-08 2026-08-15
Historial de precios
Actualizado elPrecio
2026-08-08117,69
2026-08-15117,69
Vendedor Product price Delivery Total Disponibilidad Updated
SP SpringerNatureLink Shop INT 21 449,00 JPY free 21 449,00 JPY Disponible hace 22 horas View offer
SP Springer Nature Author 21 449,00 JPY 19,00 JPY 21 468,00 JPY Disponible hace 1 semana View offer
SP SpringerNatureLink Shop INT 149,99 USD 25,00 USD 174,99 USD Disponible hace 1 día View offer
SP SpringerNatureLink Shop INT 169,99 USD 15,00 USD 184,99 USD Disponible hace 1 día View offer
SP SpringerNatureLink Shop INT 169,99 USD 15,00 USD 184,99 USD Disponible hace 1 día View offer
SP SpringerNatureLink Shop INT 177,00 EUR free 177,00 EUR Disponible hace 1 día View offer

Los precios y la disponibilidad pueden cambiar. Última actualización: 08.08.2026 23:28.

0,0
☆☆☆☆☆
0 reviews
5★ 0%
4★ 0%
3★ 0%
2★ 0%
1★ 0%

Product reviews

Rating
No reviews yet — be the first!
This book reviews a blend of artificial intelligence (AI) approaches that can take e-learning to the next level by adding value through customization. It investigates three methods: crowdsourcing via social networks; user profiling through machine learning techniques, and personal learning portfolios using learning analytics. Technology and education have drawn closer together over the years as they complement each other within the domain of e-learning, and different generations of online education reflect the evolution of new technologies as researcher and developers continuously seek to optimize the electronic medium to enhance the effectiveness of e-learning. Artificial intelligence (AI) for e-learning promises personalized online education through a combination of different intelligent techniques that are grounded in established learning theories while at the same time addressing a number of common e-learning issues. This book is intended for education technologists and e-learning researchers as well as for a general readership interested in the evolution of online education based on techniques like machine learning, crowdsourcing, and learner profiling that can be merged to characterize the future of personalized e-learning.

Similar products