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Báo cáo khoa học: "Word Maturity: Computational Modeling of Word Knowledge"

While computational estimation of difficulty of words in the lexicon is useful in many educational and assessment applications, the concept of scalar word difficulty and current corpus-based methods for its estimation are inadequate. We propose a new paradigm called word meaning maturity which tracks the degree of knowledge of each word at different stages of language learning. We present a computational algorithm for estimating word maturity, based on modeling language acquisition with Latent Semantic Analysis. . | Word Maturity Computational Modeling of Word Knowledge Kirill Kireyev Thomas K Landauer Pearson Education Knowledge Technologies Boulder CO kirill.kireyev tom.landauer @pearson.com Abstract While computational estimation of difficulty of words in the lexicon is useful in many educational and assessment applications the concept of scalar word difficulty and current corpus-based methods for its estimation are inadequate. We propose a new paradigm called word meaning maturity which tracks the degree of knowledge of each word at different stages of language learning. We present a computational algorithm for estimating word maturity based on modeling language acquisition with Latent Semantic Analysis. We demonstrate that the resulting metric not only correlates well with external indicators but captures deeper semantic effects in language. 1 Motivation It is no surprise that through stages of language learning different words are learned at different times and are known to different extents. For example a common word like dog is familiar to even a first-grader whereas a more advanced word like focal does not usually enter learners vocabulary until much later. Although individual rates of learning words may vary between high-and low-performing students it has been observed that children . acquire word meanings in roughly the same sequence Biemiller 2008 . The aim of this work is to model the degree of knowledge of words at different learning stages. Such a metric would have extremely useful applications in personalized educational technologies for the purposes of accurate assessment and personalized vocabulary instruction. 299 2 Rethinking Word Difficulty Previously related work in education and psychometrics has been concerned with measuring word difficulty or classifying words into different difficulty categories. Examples of such approaches include creation of word lists for targeted vocabulary instruction at various grade levels that were compiled by educational .