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  2. Predictive learning - Wikipedia

    en.wikipedia.org/wiki/Predictive_learning

    Predictive learning is a machine learning (ML) technique where an artificial intelligence model is fed new data to develop an understanding of its environment, capabilities, and limitations. This technique finds application in many areas, including neuroscience , business , robotics , and computer vision .

  3. Predictive coding - Wikipedia

    en.wikipedia.org/wiki/Predictive_coding

    This makes predictive coding similar to some other models of hierarchical learning, such as Helmholtz machines and Deep belief networks, which however employ different learning algorithms. Thus, the dual use of prediction errors for both inference and learning is one of the defining features of predictive coding.

  4. Carrel desk - Wikipedia

    en.wikipedia.org/wiki/Carrel_desk

    Carrels originated in monasteries to help contain the cacophony of roomfuls of monks reading aloud, as was the early practice. [3] Carrels are first recorded in the 13th century at Westminster Abbey, London, on the Garth side of the North Walk, though they probably existed from the late years of the 12th century.

  5. Learning centers in American elementary schools - Wikipedia

    en.wikipedia.org/wiki/Learning_centers_in...

    There are eight basic learning centers in an early childhood/elementary classroom, according to the Stephen F. Austin State University Charter School program, each structured to expand the students’ experiences in a variety of meaningful and effective ways. Each center is constructed to encompass numerous objectives, including state and ...

  6. Learning space - Wikipedia

    en.wikipedia.org/wiki/Learning_space

    Learning space or learning setting refers to a physical setting for a learning environment, a place in which teaching and learning occur. [1] The term is commonly used as a more definitive alternative to " classroom ," [ 2 ] but it may also refer to an indoor or outdoor location, either actual or virtual.

  7. Rule-based machine learning - Wikipedia

    en.wikipedia.org/wiki/Rule-based_machine_learning

    Rule-based machine learning (RBML) is a term in computer science intended to encompass any machine learning method that identifies, learns, or evolves 'rules' to store, manipulate or apply. [ 1 ] [ 2 ] [ 3 ] The defining characteristic of a rule-based machine learner is the identification and utilization of a set of relational rules that ...

  8. Rules extraction system family - Wikipedia

    en.wikipedia.org/wiki/Rules_extraction_system_family

    The rules extraction system (RULES) family is a family of inductive learning that includes several covering algorithms. This family is used to build a predictive model based on given observation. It works based on the concept of separate-and-conquer to directly induce rules from a given training set and build its knowledge repository.

  9. Universal Design for Learning - Wikipedia

    en.wikipedia.org/wiki/Universal_Design_for_Learning

    Universal Design for Learning is referred to by name in American legislation, such as the Higher Education Opportunity Act (HEOA) of 2008 (Public Law 110-315), [5] the 2004 reauthorization of the Individuals with Disabilities Education Act (IDEA), and the Assistive Technology Act of 1998.