@inproceedings{osika-etal-2018-second,
title = "Second Language Acquisition Modeling: An Ensemble Approach",
author = "Osika, Anton and
Nilsson, Susanna and
Sydorchuk, Andrii and
Sahin, Faruk and
Huss, Anders",
editor = "Tetreault, Joel and
Burstein, Jill and
Kochmar, Ekaterina and
Leacock, Claudia and
Yannakoudakis, Helen",
booktitle = "Proceedings of the Thirteenth Workshop on Innovative Use of {NLP} for Building Educational Applications",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-0525/",
doi = "10.18653/v1/W18-0525",
pages = "217--222",
abstract = "Accurate prediction of students' knowledge is a fundamental building block of personalized learning systems. Here, we propose an ensemble model to predict student knowledge gaps. Applying our approach to student trace data from the online educational platform Duolingo we achieved highest score on all three datasets in the 2018 Shared Task on Second Language Acquisition Modeling. We describe our model and discuss relevance of the task compared to how it would be setup in a production environment for personalized education."
}
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<abstract>Accurate prediction of students’ knowledge is a fundamental building block of personalized learning systems. Here, we propose an ensemble model to predict student knowledge gaps. Applying our approach to student trace data from the online educational platform Duolingo we achieved highest score on all three datasets in the 2018 Shared Task on Second Language Acquisition Modeling. We describe our model and discuss relevance of the task compared to how it would be setup in a production environment for personalized education.</abstract>
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%0 Conference Proceedings
%T Second Language Acquisition Modeling: An Ensemble Approach
%A Osika, Anton
%A Nilsson, Susanna
%A Sydorchuk, Andrii
%A Sahin, Faruk
%A Huss, Anders
%Y Tetreault, Joel
%Y Burstein, Jill
%Y Kochmar, Ekaterina
%Y Leacock, Claudia
%Y Yannakoudakis, Helen
%S Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F osika-etal-2018-second
%X Accurate prediction of students’ knowledge is a fundamental building block of personalized learning systems. Here, we propose an ensemble model to predict student knowledge gaps. Applying our approach to student trace data from the online educational platform Duolingo we achieved highest score on all three datasets in the 2018 Shared Task on Second Language Acquisition Modeling. We describe our model and discuss relevance of the task compared to how it would be setup in a production environment for personalized education.
%R 10.18653/v1/W18-0525
%U https://aclanthology.org/W18-0525/
%U https://doi.org/10.18653/v1/W18-0525
%P 217-222
Markdown (Informal)
[Second Language Acquisition Modeling: An Ensemble Approach](https://aclanthology.org/W18-0525/) (Osika et al., BEA 2018)
ACL
- Anton Osika, Susanna Nilsson, Andrii Sydorchuk, Faruk Sahin, and Anders Huss. 2018. Second Language Acquisition Modeling: An Ensemble Approach. In Proceedings of the Thirteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 217–222, New Orleans, Louisiana. Association for Computational Linguistics.