A Blended Grammar Learning System Featuring Unsupervised Pattern Discovery

Recent developments in cognitive and psycholinguistic research postulate that language learning is essentially the learning of grammatical construc-tions. An important type of grammatical construction with wide-ranging pedagogical implications is grammar patterns as laid out in Pattern Gram-mar. While grammar patterns have seen increasing adoption in language pedagogy, existing applications typically follow a paper-based, teacher-centered approach to instruction, which is known to be less effective in grammar learning than blended, learner-centered approaches. In this paper, we propose a blended learning model that integrates web-based technology with classroom-based instruction to facilitate efficient, personalized grammar learning. We present the design and implementation of a blended grammar learning system that provides customizable learning materials for individual learners by discovering important grammar patterns from corpora in an unsupervised manner. Preliminary evaluation shows that the proposed system achieves an accuracy in pattern discovery comparable to systems that rely on manually precompiled pattern lists and hard-coded rules. With a flexible architecture and an easy-to-use interface, the system can play a key role in the creation of a blended learning environment that can be integrated into a wide range of language learning curricula.