Predicting Second Language Learner Successes and Mistakes by Means of Conjunctive Features

Yves Bestgen


Abstract
This paper describes the system developed by the Centre for English Corpus Linguistics for the 2018 Duolingo SLAM challenge. It aimed at predicting the successes and mistakes of second language learners on each of the words that compose the exercises they answered. Its main characteristic is to include conjunctive features, built by combining word ngrams with metadata about the user and the exercise. It achieved a relatively good performance, ranking fifth out of 15 systems. Complementary analyses carried out to gauge the contribution of the different sets of features to the performance confirmed the usefulness of the conjunctive features for the SLAM task.
Anthology ID:
W18-0542
Volume:
Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Venues:
BEA | NAACL | WS
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
349–355
Language:
URL:
https://www.aclweb.org/anthology/W18-0542
DOI:
10.18653/v1/W18-0542
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PDF:
http://aclanthology.lst.uni-saarland.de/W18-0542.pdf