Streamlining Poetry Assignment Submission: How Padlet AI Improves Accessibility and Efficiency for Indonesian ELT Learners

Abstract

The rapid integration of artificial intelligence into collaborative digital platforms has opened new possibilities for streamlining literature-based assignments in English language teaching. This study examines how Padlet, a cloud-based collaborative wall equipped with generative artificial intelligence features, influences accessibility and efficiency in poetry assignment submission among Indonesian undergraduate students studying English language teaching. The objective was to determine student perceptions of the platform's usefulness for managing poetry assignments and to explore the experiences underlying those perceptions. A convergent mixed-methods design was employed, combining quantitative data from a twenty-item Likert-scale questionnaire completed by twenty-six sixth-semester students with qualitative data from semi-structured interviews involving seven students. Descriptive statistics revealed that respondents rated the platform most favorably on accessibility and ease of use, with a mean score of 4.37, and least favorably, though still positively, on efficiency and time-saving, with a mean score of 3.88, yielding an overall grand mean of 4.08 across all items. Thematic analysis of the interviews produced recurring themes centered on platform accessibility, task efficiency, support for understanding poetic devices, and peer collaboration, alongside concerns about unstable internet connectivity and occasionally generic artificial intelligence suggestions. Students consistently viewed the platform as a scaffold rather than a substitute for independent literary interpretation. The findings suggest the platform can reduce the logistical burden of poetry assignments preserving space for authentic literary engagement, with practical implications for lecturers designing technology-assisted literature instruction in higher education.