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  2. Massive open online course - Wikipedia

    en.wikipedia.org/wiki/Massive_open_online_course

    In addition, the results support the hypothesis that there is an association between the self-directed learning class the student belongs to with the significantly different course completion rate or course achievement (course achievement was measured by the completion of the online courses, the final online course grade and the cumulative GPA).

  3. Unschooling - Wikipedia

    en.wikipedia.org/wiki/Unschooling

    Unschooling is a belief of self-driven informal learning characterized by a lesson-free and curriculum-free implementation of homeschooling. [1] Unschooling encourages exploration of activities initiated by the children themselves, under the belief that the more personal learning is, the more meaningful, well-understood, and therefore useful it is to the child.

  4. E-learning (theory) - Wikipedia

    en.wikipedia.org/wiki/E-learning_(theory)

    Salmon developed a five-stage model of e-learning and e-moderating that for some time has had a major influence where online courses and online discussion forums have been used. [67] In her five-stage model, individual access and the ability of students to use the technology are the first steps to involvement and achievement.

  5. Learning - Wikipedia

    en.wikipedia.org/wiki/Learning

    Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences. [1] The ability to learn is possessed by humans, non-human animals, and some machines; there is also evidence for some kind of learning in certain plants. [2]

  6. Zero-shot learning - Wikipedia

    en.wikipedia.org/wiki/Zero-shot_learning

    Zero-shot learning (ZSL) is a problem setup in deep learning where, at test time, a learner observes samples from classes which were not observed during training, and needs to predict the class that they belong to.

  7. Multimodal learning - Wikipedia

    en.wikipedia.org/wiki/Multimodal_learning

    Multimodal learning, in the context of machine learning, is a type of deep learning using multiple modalities of data, such as text, audio, or images. In contrast, unimodal models can process only one type of data, such as text (typically represented as feature vectors ) or images.

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