Work

Using generative artificial intelligence to enhance the performance of disadvantaged students in secondary education

Year: 2025

Type: article

Abstract: We show that generative AI can support disadvantaged students, improve grades, and help close the attainment gap between pupil premium (PP) and students with special education needs (SEN). It can also alleviate teacher workload, especially for PP and SEN students, by minimising marking and feedback time, enabling better lesson planning and interventions, which can enhance teacher retention and staffing. We focus on disadvantaged students with SEN and low-income families and use AI for personalised feedback and lesson planning in arts and humanities. This enables school leaders and parents to view the qualitative and quantitative student progress. The results of this study demonstrate the potential of using AI-based systems to help close the attainment gap between disadvantaged students and their peers. The intervention given to these pupils would have been an unreasonable demand on the current teacher workload in the UK.

Source: Social Sciences & Humanities Open

DOI: 10.1016/j.ssaho.2025.102110