Optimizing the Learning Order of Chinese Characters Using a Novel Topological Sort Algorithm
This work addresses a domain-specific problem for learners of Chinese, offering an incremental improvement over prior scheduling algorithms.
The paper tackles the problem of optimizing the learning order of Chinese characters by developing a novel topological sort algorithm that balances usage frequency and structural relationships, showing it outperforms existing methods.
We present a novel algorithm for optimizing the order in which Chinese characters are learned, one that incorporates the benefits of learning them in order of usage frequency and in order of their hierarchal structural relationships. We show that our work outperforms previously published orders and algorithms. Our algorithm is applicable to any scheduling task where nodes have intrinsic differences in importance and must be visited in topological order.