CLJun 18, 2019

Automatic learner summary assessment for reading comprehension

arXiv:1906.07555v11095 citations
Originality Incremental advance
AI Analysis

This provides a useful tool for assessing non-native reading comprehension, but it is incremental as it builds on existing summarization tasks.

The paper tackled the problem of automatically assessing learner summaries for reading comprehension by proposing three novel approaches, which outperformed traditional exact word match methods and achieved quality assessments close to professional examiners.

Automating the assessment of learner summaries provides a useful tool for assessing learner reading comprehension. We present a summarization task for evaluating non-native reading comprehension and propose three novel approaches to automatically assess the learner summaries. We evaluate our models on two datasets we created and show that our models outperform traditional approaches that rely on exact word match on this task. Our best model produces quality assessments close to professional examiners.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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