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Data-driven learning (DDL) is an approach to foreign language learning. Whereas most language learning is guided by teachers and textbooks, data-driven learning treats language as data and students as researchers undertaking guided discovery tasks. Underpinning this pedagogical approach is the data - information - knowledge paradigm (see DIKW ...
The direct method operates on the idea that second language learning must be an imitation of first language learning, as this is the natural way humans learn any language: a child never relies on another language to learn its first language, and thus the mother tongue is not necessary to learn a foreign language. This method places great stress ...
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 ).
The development of communicative language teaching was bolstered by these academic ideas. Before the growth of communicative language teaching, the primary method of language teaching was situational language teaching, a method that was much more clinical in nature and relied less on direct communication. In Britain, applied linguists began to ...
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.
Chinchilla contributes to developing an effective training paradigm for large autoregressive language models with limited compute resources. The Chinchilla team recommends that the number of training tokens is twice for every model size doubling, meaning that using larger, higher-quality training datasets can lead to better results on ...
The design has its origins from pre-training contextual representations, including semi-supervised sequence learning, [24] generative pre-training, ELMo, [25] and ULMFit. [26] Unlike previous models, BERT is a deeply bidirectional, unsupervised language representation, pre-trained using only a plain text corpus.
Task-based language teaching (TBLT), also known as task-based instruction (TBI), focuses on the use of authentic language to complete meaningful tasks in the target language. Such tasks can include visiting a doctor, conducting an interview, or calling customer service for help.