Manipulating the Difficulty of C-Tests
This work addresses the need for adaptive exercises in self-directed language learning and test preparation, though it appears incremental as it builds on existing C-test methods.
The paper tackled the problem of automatically adjusting the difficulty of C-tests for language learning and assessment by proposing two manipulation strategies based on gap size and distribution, and found in evaluations with 60 participants that these strategies successfully generated C-tests at the desired difficulty levels.
We propose two novel manipulation strategies for increasing and decreasing the difficulty of C-tests automatically. This is a crucial step towards generating learner-adaptive exercises for self-directed language learning and preparing language assessment tests. To reach the desired difficulty level, we manipulate the size and the distribution of gaps based on absolute and relative gap difficulty predictions. We evaluate our approach in corpus-based experiments and in a user study with 60 participants. We find that both strategies are able to generate C-tests with the desired difficulty level.