The purpose of this study was to analyze six English as a Foreign Language (EFL) learners' trajectories of discriminating near-synonyms in a data-driven learning task. Since the learners find it considerably difficult to learn subtle meaning differences of near-synonyms, corpus-based data-driven learning may provide an opportunity for them to tackle their difficulties. The study materials guided the learners to identify the differences between the four pairs of near-synonyms, categorize the concordance lines based on their findings, and generalize the findings. The six participants had notably different trajectories of discriminating near-synonyms. The qualitative analysis of the trajectories showed a tendency that the intermediate learners focused on the meanings and found the correct answer without knowing the core meaning, and the advanced learners moved further to attend to structural differences and sometimes tested their previous knowledge on the concordance data. This study implies the need for careful guidance, collaborative group works, and strategy teaching in data-driven learning tasks.