Developing and Evaluating a Computer-Assisted Near-Synonym Learning System

Despite their similar meanings, near-synonyms may have different usages in different contexts. For second language learners, such differences are not easily grasped in practical use. In this paper, we develop a computer-assisted near-synonym learning system for Chinese English-as-aSecond-Language (ESL) learners using two automatic near-synonym choice techniques: pointwise mutual information (PMI) and n-grams. The two techniques can provide useful contextual information for learners, making it easier for them to understand different usages of various English near-synonyms in a range of contexts. The system is evaluated using a vocabulary test with near-synonyms as candidate choices. Participants are required to select the best near-synonym for each question both with and without use of the system. Experimental results show that both techniques can improve participants’ ability to discriminate among nearsynonyms. In addition, participants are found to prefer to use the PMI in the test, despite n-grams providing more precise information.