Modeling Language Proficiency Using Implicit Feedback

Chris Hokamp, Rada Mihalcea, Peter Schuelke


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 student’s 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.
Anthology ID:
L14-1090
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
3983–3986
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1126_Paper.pdf
DOI:
Bibkey:
Cite (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).
Cite (Informal):
Modeling Language Proficiency Using Implicit Feedback (Hokamp et al., LREC 2014)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/1126_Paper.pdf