Detmar Meurers, Ramon Ziai, Niels Ott and Stacey Bailey
Special Issue on Free-text Automatic Evaluation. International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL). 2011.
Contextualized, meaning-based interaction in the foreign language is widely recognized as crucial for second language acquisition. Correspondingly, current exercises in foreign language teaching generally require students to manipulate both form and meaning. For Intelligent Language Tutoring Systems to support such activities, they thus must be able to evaluate the appropriateness of the meaning of a learner response for a given exercise.
We discuss such a content-assessment approach, focusing on reading comprehension exercises. We pursue the idea that a range of simultaneously available representations at different levels of complexity and linguistic abstraction provide a good empirical basis for content assessment. We show how an annotation-based NLP architecture implementing this idea can be realized and that it successfully performs on a corpus of authentic learner answers to reading comprehension questions. To support comparison and sustainable development on content assessment, we also define a general exchange format for such exercise data.
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Bibtex entry:
@Article{Meurers.Ziai.ea-11,
author = {Detmar Meurers and Ramon Ziai and Niels Ott and Stacey Bailey},
title = {Integrating Parallel Analysis Modules to Evaluate the
Meaning of Answers to Reading Comprehension Questions},
journal = {Special Issue on Free-text Automatic Evaluation.
International Journal of Continuing Engineering
Education and Life-Long Learning (IJCEELL)},
volume = {21},
number = {4},
year = {2011},
pages = {355--369},
url = {http://purl.org/dm/papers/meurers-ziai-ott-bailey-11.html}
}