2025 ACL ACL 2025

From End-Users to Co-Designers: Lessons from Teachers

Abstract

AbstractThis study presents a teacher-centered evaluation of an AI-powered reading comprehension tool, developed to support learners with language-based difficulties. Drawing on the Social Acceptance of Technology (SAT) framework, we investigate not only technical usability but also the pedagogical, ethical, and contextual dimensions of AI integration in classrooms. We explore how teachers perceive the platform’s alignment with inclusive pedagogies, instructional workflows, and professional values through a mixed-methods approach, including questionnaires and focus groups with educators. Findings a shift from initial curiosity to critical, practice-informed reflection, with trust, transparency, and adaptability emerging as central concerns. The study contributes a replicable evaluation framework and highlights the importance of engaging teachers as co-designers in the development of educational technologies.

🌉 Interdisciplinary Bridge — Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — mixed-methods evaluation
🐝 Cross-Pollinator — Artificial Intelligence, Computer Vision, Data Science & Analytics, Interdisciplinary, Machine Learning, Natural Language Processing