This empirical investigation rigorously evaluated the teaching potential of Data-Driven Learning (DDL) for enhancing the ability of learners to apply 30 near-synonymous change-of-state verbs in two EFL Freshman English courses in a college setting across two semesters. In the study, 32 participants in the experimental group and 22 in the control group were involved in two distinct educational approaches: Data-Driven Learning (DDL) guided by constructivism, facilitated by the Corpus of Contemporary American English (COCA), and conventional rule-based instruction, respectively. The students' skill levels were measured at three separate stages: pre-intervention, post-intervention, and a delayed post-intervention (3 months). The quantitative findings revealed that DDL notably strengthened learners' collocational competence following the intervention, with the effect enduring even 3 months later. However, the impact was not substantial for high-complexity verbs. Additionally, DDL seemed to promote a varied utilization of collocates of a singular node word by students in the experimental group, a result maintained at the delayed posttest. The paper concludes with an exploration of the pedagogical consequences of DDL, specifically in relation to collocation instruction for English as a Foreign Language (EFL) learners. The insights emphasize the potential of DDL as an efficacious language education instrument, underscoring its importance in boosting the linguistic aptitude of EFL learners within academic contexts. Hence, the study accentuates DDL's anticipated function in the instructional framework of second language acquisition, calling for additional scrutiny to refine its execution.