THE IMPACT OF AI-POWERED CONTEXTUAL DESCRIPTIONS ON VOCABULARY ACQUISITION: A PILOT CASE STUDY

This study investigates the potential effects of an AI-driven web browser extension named “TooMuchTalk” on vocabulary learning and reading comprehension of English language learners. English language learners frequently search for unknown vocabulary on the internet while reading long texts. This constant look-up situation may lead to loss of focus, increasing anxiety toward reading long texts and cognitive load. To measure the effects of the extension, a five-day study was conducted with a pre- and post-tests design involving nine English Language Teaching (ELT) students. The quantitative findings indicated a significant difference in the number of saved words between pre and post-tests (M_pre = 0.89, SD_pre = 1.36, M_post = 12.67, SD_post = 13.31, t(8) = -2.60, p = .031). Contextualized translations and one of the key features of the extension called “AI Tutor” were observed to support learners by reducing mental fatigue and supporting sustained engagement. Despite the findings, users have faced some user experience (UX) challenges that need to be fixed, including issues with audio integration. However, overall the extension appears to support motivation and may help reduce problems such as losing focus, switching tabs and cognitive load.