Grammar Exercise

Research on automated grammar exercise generation focuses on creating effective and efficient tools for language learning and assessment. Current approaches leverage techniques like neural networks and context-free grammars to automatically generate exercises from various text sources, including adapting existing texts into gap-filling exercises or creating multiple-choice questions targeting specific grammatical structures. This work addresses challenges in data annotation and algorithm design, aiming to improve both the quality and quantity of available grammar exercises, particularly for under-resourced languages. The resulting tools have the potential to significantly enhance language learning applications and educational resources.