<![CDATA[Generative AI (GenAI) has increasingly been incorporated into higher education and language learning because of its potential to provide immediate explanations, examples, and interactive support. In Sociolinguistics, however, limited research has examined how Generative AI supports students’ understanding of language variation concepts, particularly in Indonesian higher education contexts. To address this gap, this study investigated how students used Generative AI in a Sociolinguistics course and the extent to which it enhanced their understanding of language variation concepts at UIN Raden Intan Lampung. This study employed an explanatory sequential mixed-methods design. The participants were 32 undergraduate students enrolled in a Sociolinguistics course. The instruments consisted of a language variation concept test, a GenAI use questionnaire, weekly learning logs, and semi-structured interviews. Data were collected over six weeks through pretest and posttest administration, questionnaire distribution, learning-log documentation, and follow-up interviews with selected students. Quantitative data were analyzed using descriptive statistics and a paired-samples t-test, while qualitative data were analyzed thematically. The findings showed that students’ posttest scores (M = 69.75, SD = 10.81) were significantly higher than their pretest scores (M = 58.84, SD = 7.24), t(31) = 6.45, p < .001, with a large effect size (Cohen’s dz = 1.14). The qualitative findings revealed that students mainly used Generative AI to simplify difficult concepts, generate contextualized examples, refine their understanding through follow-up prompts, and verify AI-generated responses. Overall, Generative AI functioned as a supportive learning resource in Sociolinguistics, although its effectiveness depended on students’ critical and strategic use.]]>
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