Teacher Perception of Automatically Extracted Grammar Concepts for L2 Language Learning
Aditi Chaudhary, Arun Sampath, Ashwin Sheshadri, Antonios, Anastasopoulos, Graham Neubig

TL;DR
This paper introduces an automatic framework that extracts and visualizes grammatical and semantic descriptions from text corpora to aid language teachers, especially for under-resourced languages like Kannada and Marathi.
Contribution
It presents a novel automated method for discovering and visualizing language rules from corpora, reducing manual effort in curriculum development for less-resourced languages.
Findings
Teachers found the extracted materials useful for lesson preparation.
The framework successfully identified key grammatical and semantic features.
Educators considered the materials interesting and potentially beneficial for learner evaluation.
Abstract
One of the challenges of language teaching is how to organize the rules regarding syntax, semantics, or phonology of the language in a meaningful manner. This not only requires pedagogical skills, but also requires a deep understanding of that language. While comprehensive materials to develop such curricula are available in English and some broadly spoken languages, for many other languages, teachers need to manually create them in response to their students' needs. This process is challenging because i) it requires that such experts be accessible and have the necessary resources, and ii) even if there are such experts, describing all the intricacies of a language is time-consuming and prone to omission. In this article, we present an automatic framework that aims to facilitate this process by automatically discovering and visualizing descriptions of different aspects of grammar.…
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Taxonomy
TopicsNatural Language Processing Techniques · Second Language Acquisition and Learning · Text Readability and Simplification
