Restoring Student Voice in AI-Assisted Assignments

Closed

Pramana, Prahastiwi Utari, Adi Inggit Handoko, Monika Sri Yuliarti, Anam Miftakhul Huda, Vinda Maya Setianingrum, Tri Susanto

2026 College Teaching Article Cited by 0

Abstract

This Quick Fix article addresses a growing problem in higher education: student writing that appears polished and efficient with AI assistance but often lacks depth, contextual sensitivity, and authentic voice. This issue is especially important in reflective, applied, and discussion-based assignments, where students are expected to demonstrate not only fluent prose but also ethical judgment, self-reflection, and awareness of how ideas affect people, communities, and real situations. To respond to this challenge, the article introduces the Voice, Judgment, and Context Check, an instructor-designed classroom technique that helps students preserve personal voice, make transparent decisions about AI use, and reconnect written work with disciplinary and lived contexts. The technique consists of three brief components: a pre-writing personal anchor, an AI use note with justification, and a human revision paragraph. Together, these steps encourage students to link course concepts with lived experience, disclose how they used AI, and identify what remains distinctly their own. Rather than banning AI, this approach extends existing assignments without major curricular restructuring and offers instructors across disciplines a practical way to preserve student voice, visible judgment, and meaningful context in AI-assisted work. © 2026 Taylor & Francis Group, LLC.

Affiliations

Communication Department, Universitas Sebelas Maret, Surakarta, Indonesia; Communication Department, Universitas Sriwijaya, Palembang, Indonesia; Communication Department, Universitas Negeri Surabaya, Surabaya, Indonesia; Communication Department, Universitas Singaperbangsa Karawang, Karawang, Indonesia