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Exploring AI-Assisted Feedback: A Case Study in English Education at City of Wolverhampton College

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Case Study
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Hayley Jarman

Lecturer in English GCSE at Inner City College

At City of Wolverhampton College, English teacher Hayley Jarman innovated assessment feedback using Chat GPT. Aligning with a digital skills initiative, she integrated AI for marking student work. The experiment revealed strengths in efficient, comprehensive feedback but highlighted challenges in tone and empathetic communication, underscoring the nuanced nature of effective feedback in education.

Hayley Jarman, an English teacher, utilised Chat GPT to mark student essays and provide feedback during a digital skills-themed class.

She fed the AI system the exam board's mark scheme and student submissions. Chat GPT quickly generated marks and comprehensive feedback, including suggested rewrites. While the AI's efficiency and thoroughness were notable, student reactions varied. Some appreciated the detailed feedback, while others found the AI's tone harsh and lacking empathy.

This experiment raised critical reflections on what constitutes effective feedback. While Chat GPT's feedback was technically accurate and detailed, it sometimes missed the nuanced human element necessary for student engagement and understanding.

This case illustrates the potential and limitations of AI in educational settings, particularly in subjective fields like English, where personalisation and empathetic communication play significant roles.

The scenario in this case study is genuine and based upon real events and data, however its narration has been crafted by AI to uphold a standardised and clear format for readers.

Key Learning

AI can efficiently provide detailed, comprehensive feedback, aligning with technical criteria. The tone and human touch in feedback are crucial, areas where AI currently falls short. Student reception to AI-generated feedback varies, indicating a need for a balanced approach. The role of AI in education should be carefully considered, especially in subjects requiring subjective judgement and empathy.


Over-reliance on AI for feedback can lead to a lack of personalised, empathetic communication. Discrepancies between AI and teacher evaluations may cause confusion or dissatisfaction among students. Sole reliance on AI feedback might overlook the subjective, individualized nature of learning. Potential resistance from students towards AI feedback, impacting their engagement and learning experience.