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Using generative artificial intelligence to enhance the performance of disadvantaged students in secondary education
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Soukaina Rhazzafe ,
Raymond Moodley ,
Stefan Kuhn ,
Fabio Caraffini ,
Sara Wilford ,
Rachel Higginbottom ,
Simon Colreavy-Donnelly ,
Mario Gongora
Social Sciences & Humanities Open, Volume: 12, Start page: 102110
Swansea University Author:
Fabio Caraffini
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© 2025 The Author(s). This is an open access article under the CC BY license.
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DOI (Published version): 10.1016/j.ssaho.2025.102110
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...
| Published in: | Social Sciences & Humanities Open |
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| ISSN: | 2590-2911 |
| Published: |
Elsevier BV
2025
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa70809 |
| 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. |
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| Keywords: |
Disadvantaged pupils; Pupil premium; Feedback; Education; Large language models; Artificial intelligence; Generative AI |
| College: |
Faculty of Science and Engineering |
| Funders: |
SR acknowledges financial support by Taighde Éireann – Research Ireland, under Grant Number 18/CRT/6223. |
| Start Page: |
102110 |