We discuss the collection and analysis of a cross-sectional and longitudinal learner corpus consisting of answers to reading comprehension questions written by adult second language learners of German. We motivate the need for such task-based learner corpora and identify the properties which make reading comprehension exercises a particularly interesting task. In terms of the creation of the corpus, we introduce the web-based WELCOME tool we developed to support the decentralized data collection and annotation of the richly structured corpus in real-life language teaching programs. On the analysis side, we investigate the binary and the complex content-assessment classification scheme used by the annotators and the inter-annotator agreement obtained for the current corpus snapshot, at the halfway point of our four-year effort. We present results showing that for such task-based corpora, meaning assessment can be performed with reasonable agreement and we discuss several sources of disagreement.
2024. Paraphrase Generation and Supervised Learning for Improved Automatic Short Answer Grading. International Journal of Artificial Intelligence in Education
Alexopoulou, Theodora, Marije Michel, Akira Murakami & Detmar Meurers
2017. Task Effects on Linguistic Complexity and Accuracy: A Large‐Scale Learner Corpus Analysis Employing Natural Language Processing Techniques. Language Learning 67:S1 ► pp. 180 ff.
Meurers, Detmar & Markus Dickinson
2017. Evidence and Interpretation in Language Learning Research: Opportunities for Collaboration With Computational Linguistics. Language Learning 67:S1 ► pp. 66 ff.
Caroline Féry & Shinichiro Ishihara
2016. The Oxford Handbook of Information Structure,
2013. Fourth International Conference on Information and Communication Technology and Accessibility (ICTA), ► pp. 1 ff.
[no author supplied]
2018. Quality Estimation for Machine Translation [Synthesis Lectures on Human Language Technologies, ],
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