Workshop title: Pairing Peer and AI Feedback: Experimenting with the Process-Based PAIRR Model in ESP/EAP Writing
Names of presentres: Hamid Guedra, Hanna Vihava
Affiliation and academic title: Language Centre, LAB University of Applied Sciences & LUT University, Senior Lecturers
Keywords: AI feedback, peer feedback, ESP/EAP writing pedagogy, writing process, PAIRR process, critical AI literacy
Abstract:
This workshop focuses on AI and the writing process, specifically using generative AI to provide writing feedback in EAP/ESP contexts in higher education. We will introduce the PAIRR process (peer + AI review and reflection), a curricular intervention developed and piloted at the University of California, Davis, in 2023–2024 with over 650 students. We have also tested a simplified version of PAIRR in select EAP/ESP courses at the LAB/LUT Language Centre in autumn 2025, with approximately 70 students.
PAIRR was designed to integrate AI feedback into writing tasks transparently and responsibly, and it follows a five-step process: 1) draft, 2) peer feedback, 3) AI feedback, 4) reflection, and 5) revision (Figure 1). The process also typically includes discussions and short readings on AI and language equity. (Writing UC Davis, 2025)
As the process reveals, rather than replacing human feedback, PAIRR introduces AI as one tool within a broader human-centred framework. By pairing peer feedback with AI feedback, as well as instructor-guided reflection on the feedback, PAIRR can help increase student confidence and develop students’ critical AI literacy skills; the process requires students to actively make decisions, increasing their agency. (Peer & AI Review + Reflection 2025)
Before the workshop, we will provide participants with short pre-readings. During the session, we intend to briefly introduce the original PAIRR process and share our pilot results. Participants will then get hands-on experience with PAIRR by using short pre-written samples. They will provide peer feedback based on set criteria, use AI for feedback (e.g., a custom-built Google Gemini Gem), reflect on the similarities and differences between the two, and share their thoughts on the process. We hope the workshop inspires participants to begin experimenting with PAIRR in their own classrooms.
References:
Peer & AI Review + Reflection. 2025. Integrating AI Responsibly in Writing Instruction: Insights from the PAIRR Model. Cited 15 January 2025. https://pairrfeedback.substack.com/p/integrating-ai-responsibly-in-writing
Writing UC Davis. 2025. Peer & AI Review + Reflection (PAIRR). Cited 15 January 2025. https://writing.ucdavis.edu/pairr