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Bridging Literacy Gaps: The Impact of AI-Driven Personalised Learning on Reading Skills and Educational Equity. EdWorkingPaper No. 25-1209

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Bibliographic Details
Title: Bridging Literacy Gaps: The Impact of AI-Driven Personalised Learning on Reading Skills and Educational Equity. EdWorkingPaper No. 25-1209
Language: English
Authors: Pilar Cuevas-Ruiz, Luz Rello, Ismael Sanz, Almudena Sevilla, Annenberg Institute for School Reform at Brown University
Source: Annenberg Institute for School Reform at Brown University. 2025.
Availability: Annenberg Institute for School Reform at Brown University. Brown University Box 1985, Providence, RI 02912. Tel: 401-863-7990; Fax: 401-863-1290; e-mail: annenberg@brown.edu; Web site: https://annenberg.brown.edu/
Peer Reviewed: N
Page Count: 42
Publication Date: 2025
Document Type: Reports - Research
Education Level: Elementary Education
Descriptors: Artificial Intelligence, Individualized Instruction, Reading Skills, Equal Education, Computer Assisted Instruction, Foreign Countries, Computer Software, Elementary School Students, Elementary Schools, Literacy Education, Program Effectiveness, Student Characteristics, Feedback (Response)
Geographic Terms: Spain (Madrid)
Abstract: Persistent literacy skills deficits hinder educational attainment, limit labour market opportunities, and exacerbate socioeconomic inequalities. This paper evaluates the causal effect of an AI-driven Computer-Assisted Learning (CAL) program implemented by the Government of Madrid, which features personalised, adaptive content and real-time feedback on students' literacy proficiency. We leverage extensive and unique longitudinal information on student learning outcomes from the software across 264 schools over five school years and exploit exogenous variation in the timing of implementation to address possible selection into program participation and engagement. Our findings show that each additional session increases reading progress by 2.4 per cent of a standard deviation, roughly equal to one month of learning. Our findings highlight how AI-driven CAL tools can offer scalable interventions for effectively designing education policies to reduce educational inequities.
Abstractor: As Provided
Entry Date: 2025
Accession Number: ED674076
Database: ERIC
Description
Abstract:Persistent literacy skills deficits hinder educational attainment, limit labour market opportunities, and exacerbate socioeconomic inequalities. This paper evaluates the causal effect of an AI-driven Computer-Assisted Learning (CAL) program implemented by the Government of Madrid, which features personalised, adaptive content and real-time feedback on students' literacy proficiency. We leverage extensive and unique longitudinal information on student learning outcomes from the software across 264 schools over five school years and exploit exogenous variation in the timing of implementation to address possible selection into program participation and engagement. Our findings show that each additional session increases reading progress by 2.4 per cent of a standard deviation, roughly equal to one month of learning. Our findings highlight how AI-driven CAL tools can offer scalable interventions for effectively designing education policies to reduce educational inequities.