@inproceedings{hokamp-etal-2014-modeling,
title = "Modeling Language Proficiency Using Implicit Feedback",
author = "Hokamp, Chris and
Mihalcea, Rada and
Schuelke, Peter",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/1126_Paper.pdf",
pages = "3983--3986",
abstract = "We describe the results of several experiments with interactive interfaces for native and L2 English students, designed to collect implicit feedback from students as they complete a reading activity. In this study, implicit means that all data is obtained without asking the user for feedback. To test the value of implicit feedback for assessing student proficiency, we collect features of user behavior and interaction, which are then used to train classification models. Based upon the feedback collected during these experiments, a students performance on a quiz and proficiency relative to other students can be accurately predicted, which is a step on the path to our goal of providing automatic feedback and unintrusive evaluation in interactive learning environments.",
}
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%0 Conference Proceedings
%T Modeling Language Proficiency Using Implicit Feedback
%A Hokamp, Chris
%A Mihalcea, Rada
%A Schuelke, Peter
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F hokamp-etal-2014-modeling
%X We describe the results of several experiments with interactive interfaces for native and L2 English students, designed to collect implicit feedback from students as they complete a reading activity. In this study, implicit means that all data is obtained without asking the user for feedback. To test the value of implicit feedback for assessing student proficiency, we collect features of user behavior and interaction, which are then used to train classification models. Based upon the feedback collected during these experiments, a students performance on a quiz and proficiency relative to other students can be accurately predicted, which is a step on the path to our goal of providing automatic feedback and unintrusive evaluation in interactive learning environments.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/1126_Paper.pdf
%P 3983-3986
Markdown (Informal)
[Modeling Language Proficiency Using Implicit Feedback](http://www.lrec-conf.org/proceedings/lrec2014/pdf/1126_Paper.pdf) (Hokamp et al., LREC 2014)
ACL
- Chris Hokamp, Rada Mihalcea, and Peter Schuelke. 2014. Modeling Language Proficiency Using Implicit Feedback. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 3983–3986, Reykjavik, Iceland. European Language Resources Association (ELRA).