{"title":"TextMix: using NLP and APIs to generate chunked sentence scramble\n tasks","authors":"Brendon Albertson","doi":"10.14705/rpnet.2021.54.1300","DOIUrl":null,"url":null,"abstract":"A Computer-Assisted Language Learning (CALL) application, TextMix, was\n developed as a proof-of-concept for applying Natural Language Processing\n (NLP) sentence chunking techniques to creating ‘sentence scramble’ learning\n tasks. TextMix addresses limitations of existing applications for creating\n sentence scrambles by using NLP to parse and scramble syntactic components\n of sentences, while connecting with Application Programming Interfaces\n (APIs) to provide repeated exposure to authentic sentences in the context of\n texts such as Wikipedia articles. In addition to identifying a novel\n application of NLP and APIs in CALL, this project highlights the need for\n teacher-friendly interfaces that prioritize pedagogically useful ways of\n chunking text.","PeriodicalId":350173,"journal":{"name":"CALL and professionalisation: short papers from EUROCALL 2021","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"CALL and professionalisation: short papers from EUROCALL 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14705/rpnet.2021.54.1300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A Computer-Assisted Language Learning (CALL) application, TextMix, was
developed as a proof-of-concept for applying Natural Language Processing
(NLP) sentence chunking techniques to creating ‘sentence scramble’ learning
tasks. TextMix addresses limitations of existing applications for creating
sentence scrambles by using NLP to parse and scramble syntactic components
of sentences, while connecting with Application Programming Interfaces
(APIs) to provide repeated exposure to authentic sentences in the context of
texts such as Wikipedia articles. In addition to identifying a novel
application of NLP and APIs in CALL, this project highlights the need for
teacher-friendly interfaces that prioritize pedagogically useful ways of
chunking text.