Supplement of the article:

Automatic online writing support for L2 learners of German through output monitoring by a natural-language paraphrase generator.

Karin Harbusch and Gerard Kempen.

In: Mike Levy, Françoise Blin, Claire Bradin Siskin and Osamu Takeuchi (eds.),
WORLDCALL - International Perspective on Computer-Assisted Language Learning, Routledge, New York, NY, 2011.


Students who are learning to write in a foreign language, often want feedback on the grammatical quality of the sentences they produce. The usual NLP approach to this problem is based on parsing student-generated text. Here, we propose a generation-based approach aiming at preventing errors (scaffolding). In our ICALL system, the student constructs sentences by composing syntactic trees out of lexically anchored treelets via a graphical drag-and-drop user interface. A natural-language generator computes all possible grammatically well-formed sentences entailed by the student-composed tree. It provides positive feedback if the student-composed tree belongs to the well-formed set, and negative feedback otherwise. If so requested by the student, it can substantiate the positive or negative feedback based on a comparison between the student-composed tree and its own trees (informative feedback on demand). In case of negative feedback, the system refuses to build the structure attempted by the student. Frequently occurring errors are handled in terms of malrules. The system we describe is a prototype (implemented in JAVA and C++) which can be parameterized with respect to L1 and L2, the size of the lexicon, and the level of detail of the visually presented grammatical structures.


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