Report
Access Is Not Enough: Human Support Improves Engagement with AI Tutoring. EdWorkingPaper No. 26-1451
| Title: | Access Is Not Enough: Human Support Improves Engagement with AI Tutoring. EdWorkingPaper No. 26-1451 |
|---|---|
| Language: | English |
| Authors: | Carly D. Robinson, David Gormley, Ana Trindade Ribeiro, Susanna Loeb, Annenberg Institute for School Reform at Brown University |
| Source: | Annenberg Institute for School Reform at Brown University. 2026. |
| 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: | 28 |
| Publication Date: | 2026 |
| Sponsoring Agency: | Accelerate Smith Richardson Foundation |
| Document Type: | Reports - Research Numerical/Quantitative Data |
| Education Level: | Elementary Education |
| Descriptors: | Artificial Intelligence, Technology Uses in Education, Intelligent Tutoring Systems, Individualized Instruction, Elementary School Students, Tutors, Reading Achievement, Reading Instruction, Instructional Effectiveness, Cross Age Teaching |
| Abstract: | AI tutoring platforms offer a promising path to scaling personalized instruction, but only if students use them. We report findings from two randomized controlled trials in which elementary students were assigned to use an AI literacy platform independently or with an in-person tutor focused on engagement, not direct instruction. Despite dedicated session time, nearly half of students in the control group never used the platform, and those who did averaged only 2-5 minutes per week. Working with human tutors increased average weekly platform usage by 1 to 4 minutes and engagement by 71-80%. However, usage remained low, and the intervention did not improve reading achievement. Findings suggest that access alone is insufficient; implementation and human support matter for promoting meaningful engagement with AI-based learning tools. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | ED681902 |
| Database: | ERIC |
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