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2. Interactive Learning - Wikipedia

   en.wikipedia.org/wiki/Interactive_Learning

   Interactive learning is a pedagogical approach that incorporates social networking and urban computing into course design and delivery. It has emerged as a result of the widespread use of digital technology and virtual communication among students. The integration of digital media in education has contributed to the popularity and reliance on ...

3. Adaptive learning - Wikipedia

   en.wikipedia.org/wiki/Adaptive_learning

   Adaptive learning, also known as adaptive teaching, is an educational method which uses computer algorithms as well as artificial intelligence to orchestrate the interaction with the learner and deliver customized resources and learning activities to address the unique needs of each learner. [1] In professional learning contexts, individuals ...

4. Synchronous learning - Wikipedia

   en.wikipedia.org/wiki/Synchronous_learning

   Synchronous learning refers to a learning event in which a group of students are engaging in learning at the same time. Before learning technology allowed for synchronous learning environments, most online education took place through asynchronous learning methods. Since synchronous tools that can be used for education have become available ...

5. Perceptual learning - Wikipedia

   en.wikipedia.org/wiki/Perceptual_learning

   Perceptual learning is defined as a "change in perception as a product of experience, and has reviewed evidence demonstrating that discrimination between otherwiords. that sound similar to their native language. They now can tell the difference whereas in category learning they are trying to separate the two.

6. AOL Mail

   mail.aol.com

   Absolutely! It's quick and easy to sign up for a free AOL account. With your AOL account you get features like AOL Mail, news, and weather for free!

7. Generative adversarial network - Wikipedia

   en.wikipedia.org/wiki/Generative_adversarial_network

   Transfer learning. State-of-art transfer learning research use GANs to enforce the alignment of the latent feature space, such as in deep reinforcement learning. This works by feeding the embeddings of the source and target task to the discriminator which tries to guess the context.