Paper Info
Title
Adaptive System for Language Learning
Abstract
This paper presents a system that combines NLP and hand-written rules for enhancing the text of authentic Web pages based on the needs of a specific language learner. It uses the Stanford CoreNLP system to process texts, and applies hand-written rules for retrieving language information that is relevant according to a given Common European Framework of Reference for Languages (CEFR) level. After the text content of the Web page is processed, it is presented to the user with enhancements of various language structure. These enhancements are meant to draw the user's attention to linguistic structures that are present on the text, so that the reading activity does not encompass only the meaning of the text, but also serves as a reinforcement to language learning activities.
Year
DOI
Venue
2017
10.1109/ICALT.2017.46
2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT)
Keywords
Field
DocType
Computational Linguistics,NLP,Adaptive System,Second Language Learning,CALL
Pragmatics,Web page,Common European Framework of Reference for Languages,Computer science,Adaptive system,Language acquisition,Language identification,Natural language processing,Artificial intelligence
Conference
ISSN
ISBN
Citations 
2161-3761
978-1-5386-3871-2
1
PageRank 
References 
Authors
0.38
2
2
Name
Order
Citations
PageRank
Leonardo Zilio188.69
Cédrick Fairon212115.14