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  2. ChatGPT in education - Wikipedia

    en.wikipedia.org/wiki/ChatGPT_in_education

    The education technology company Chegg, which was a website dedicated to helping students with assignments using a database of collected worksheets and assignments, became one of the most prominent business victims to ChatGPT, with its stock price nearly being cut in half after a quarterly earnings call in May 2023. [17] [18]

  3. Reading comprehension - Wikipedia

    en.wikipedia.org/wiki/Reading_comprehension

    Deep processing involves semantic processing, which happens when we encode the meaning of a word and relate it to similar words. Shallow processing involves structural and phonemic recognition, the processing of sentence and word structure, i.e. first-order logic , and their associated sounds.

  4. Deeper learning - Wikipedia

    en.wikipedia.org/wiki/Deeper_Learning

    The blog articles are written pro bono by major educational writers who advocate for the paradigm shift to Deeper Learning as well as by a balance of school leaders, teachers, professional learning specialists and others who are incorporating deeper learning practices into their curricula, instruction, assessment and system change plans.

  5. Deep linguistic processing - Wikipedia

    en.wikipedia.org/wiki/Deep_linguistic_processing

    Deep linguistic processing is a natural language processing framework which draws on theoretical and descriptive linguistics. It models language predominantly by way of theoretical syntactic/semantic theory (e.g. CCG , HPSG , LFG , TAG , the Prague School ).

  6. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    Furthermore, researchers involved in exploring learning algorithms for neural networks are gradually uncovering generic principles that allow a learning machine to be successful. For example, Bengio and LeCun (2007) wrote an article regarding local vs non-local learning, as well as shallow vs deep architecture. [231]

  7. Artificial grammar learning - Wikipedia

    en.wikipedia.org/wiki/Artificial_grammar_learning

    The AI programs first adapted to simulate both natural and artificial grammar learning used the following basic structure: Given A set of grammatical sentences from some language. Find A procedure for recognizing and/or generating all grammatical sentences in that language. An early model for AI grammar learning is Wolff's SNPR System.

  8. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.

  9. Minimalist program - Wikipedia

    en.wikipedia.org/wiki/Minimalist_program

    English is a left-headed language, such that the element on the left is the head; Japanese is a right-headed language, such that the element on the right is the head. Merge (a critical operation in MP) can account for the patterns of word-combination, and more specifically word-order, observed in children's first language acquisition .

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