TY - GEN
T1 - Learner corpus and its application to automatic level checking using machine learning algorithms
AU - Hasan, Md Maruf
AU - Hnin, Oo Khaing
PY - 2008
Y1 - 2008
N2 - A learner corpus is a computerized textual database of the language produced by foreign language learners. Annotated learner corpora contain invaluable meta-information about learners and the errors they make. With proper feature extractions and machine learning techniques, it is possible to extract implicit and explicit knowledge from learner corpora and develop useful applications to support effective foreign language teaching and learning, such as automatic proficiency level checking, error-driven and personalized learning etc. In this paper, we use a learner corpus and experiment with feature extraction and machine learning techniques to explore such applications. In particular, we reported our experimental results in automatic proficiency checking with ID3 and C4.5 Decision Tree algorithms, Bayesian Net and SVM. We also briefly outline other potential applications of learner corpora such as in error-driven learning by using implicit and explicit features along with machine learning.
AB - A learner corpus is a computerized textual database of the language produced by foreign language learners. Annotated learner corpora contain invaluable meta-information about learners and the errors they make. With proper feature extractions and machine learning techniques, it is possible to extract implicit and explicit knowledge from learner corpora and develop useful applications to support effective foreign language teaching and learning, such as automatic proficiency level checking, error-driven and personalized learning etc. In this paper, we use a learner corpus and experiment with feature extraction and machine learning techniques to explore such applications. In particular, we reported our experimental results in automatic proficiency checking with ID3 and C4.5 Decision Tree algorithms, Bayesian Net and SVM. We also briefly outline other potential applications of learner corpora such as in error-driven learning by using implicit and explicit features along with machine learning.
KW - Annotated learner corpora
KW - Automatic proficiency level checking
KW - Computer-assisted language learning (CALL)
KW - Foreign language pedagogy
UR - http://www.scopus.com/inward/record.url?scp=52949103648&partnerID=8YFLogxK
U2 - 10.1109/ECTICON.2008.4600364
DO - 10.1109/ECTICON.2008.4600364
M3 - Conference Proceeding
AN - SCOPUS:52949103648
SN - 1424421012
SN - 9781424421015
T3 - 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2008
SP - 25
EP - 28
BT - 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2008
T2 - 5th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2008
Y2 - 14 May 2008 through 17 May 2008
ER -