Language Muse: Automated Linguistic Activity Generation for English Language Learners
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| Title: | Language Muse: Automated Linguistic Activity Generation for English Language Learners |
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| Language: | English |
| Authors: | Madnani, Nitin, Burstein, Jill, Sabatini, John, Biggers, Kietha, Andreyev, Slava |
| Source: | Grantee Submission. 2016. |
| Peer Reviewed: | Y |
| Page Count: | 6 |
| Publication Date: | 2016 |
| Sponsoring Agency: | Institute of Education Sciences (ED) |
| Contract Number: | R305A140472 |
| Document Type: | Reports - Descriptive Speeches/Meeting Papers |
| Descriptors: | English Language Learners, Reading Instruction, Natural Language Processing, Learning Activities, Class Activities, English Instruction, Second Language Instruction, Computer Oriented Programs, Sentences, Reading Comprehension, Open Source Technology |
| Abstract: | Current education standards in the U.S. require school students to read and understand complex texts from different subject areas (e.g., social studies). However, such texts usually contain figurative language, complex phrases and sentences, as well as unfamiliar discourse relations. This may present an obstacle to students whose native language is not English -- a growing sub-population in the US. One way to help such students is to create classroom activities centered around linguistic elements found in subject area texts (DelliCarpini, 2008). We present a web-based tool that uses NLP algorithms to automatically generate customizable linguistic activities that are grounded in language learning research. |
| Abstractor: | As Provided |
| Number of References: | 17 |
| IES Funded: | Yes |
| Entry Date: | 2016 |
| Accession Number: | ED574729 |
| Database: | ERIC |
| Abstract: | Current education standards in the U.S. require school students to read and understand complex texts from different subject areas (e.g., social studies). However, such texts usually contain figurative language, complex phrases and sentences, as well as unfamiliar discourse relations. This may present an obstacle to students whose native language is not English -- a growing sub-population in the US. One way to help such students is to create classroom activities centered around linguistic elements found in subject area texts (DelliCarpini, 2008). We present a web-based tool that uses NLP algorithms to automatically generate customizable linguistic activities that are grounded in language learning research. |
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