Enhancing Technical Vocabulary Learning: A Comparative Study of Reading News Posts on X and a Word List Among EFL Learners

Abstract

This study examined whether reading news posts on X, formerly Twitter, could improve EFL learners’ technical vocabulary more effectively than a traditional word-list technique. A quasi-experimental mixed-methods design was used with 40 male Saudi undergraduate English-major students at Qassim University. The participants were divided into an X-based group and a word-list group. Both groups studied the same 20 technical vocabulary items and completed a pre-test and post-test, while ten students from the X-based group were interviewed. The results showed no significant difference between the groups before the treatment, t(38) = 0.25, p = .804. After the treatment, both groups improved, but the X-based group achieved higher gains. Its mean score increased from 18.10 to 33.70, compared with the word-list group, which increased from 17.85 to 26.80. The post-test difference was statistically significant, t(38) = 5.12, p < .001, Cohen’s d = 1.62. Interview findings showed that students found X-based news posts engaging and helpful because the target words appeared in real contexts, although some posts were challenging due to unfamiliar topics and difficult vocabulary. The study concludes that carefully selected news posts on X can be a useful supplementary tool for teaching technical vocabulary in Saudi EFL classrooms.