AI Injected e-Learning
The Future of Online Education
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Beschreibung
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.
Reviews a blend of artificial intelligence (AI) approaches that can take e-learning to the next level by adding value through customization
Investigates three methods: crowdsourcing via social networks; user profiling through machine learning techniques, and personal learning portfolios using learning analytics
Aimed at researchers and academics working in computational intelligence, user profiling, machine learning, as well as e-Learning and technology enhanced learning
Reviews a blend of artificial intelligence (AI) approaches that can take e-learning to the next level by adding value through customization Investigates three methods: crowdsourcing via social networks; user profiling through machine learning techniques, and personal learning portfolios using learning analytics Aimed at researchers and academics working in computational intelligence, user profiling, machine learning, as well as e-Learning and technology enhanced learning Includes supplementary material: sn.pub/extras
Autor*in
Matthew Montebello
Themen in »AI Injected e-Learning«
Machine Learning Techniques Crowdsourcing for online education Intelligent User Profiling e-Learning customization Personal Learning Environment Learning Analytics Personal Learning Portfolio Personal Learning Network