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Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

Unsupervised tool for quantification of progress in L2 English phraseological

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DOI: http://dx.doi.org/10.15439/2017F433

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 383388 ()

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Abstract. This study aimed to aid the enormous effort required to analyze phraseological writing competence by developing an automatic evaluation tool for texts. We attempted to measure both second language (L2) writing proficiency and text quality. In our research, we adapted the CollGram technique that searches a reference corpus to determine the frequency of each pair of tokens (bi-grams) and calculates the t-score and related information. We used the Level 3 Corpus of Contemporary American English as a reference corpus. Our solution performed well in writing evaluation and is freely available as a web service or as source for other researchers.

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