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arXiv · 2609.38737

AIfred: Augmented Learning through Functional Robotic Embodiment at the Desk

Gregorio Orlando·Milan Groshev·Eduardo Castelló Ferrer
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Abstract

Desk-based learning and creative activities benefit from handwritten engagement. However, current generative AI tools deliver guidance through a separate screen, creating a gap between where users think and where assistance appears. To address this, in this work we design AIfred, a desk-based robotic arm with a projector mounted at the end-effector that places AI-generated guidance alongside handwritten work. AIfred combines workspace perception, context-aware content generation, and robot-mediated projection to support math assignments, image generation, and drawing tasks. In a user study (n = 36), we compared AIfred against ChatGPT (GPT-5.6 Luna) running on a laptop. Both tools performed comparably while assistance was available during the math assignment (6.7 vs. 7.3/10, p = .41), but AIfred improved short-term learning transfer by 60% once assistance was withdrawn (7.0 vs. 4.4/10, p = .003). In addition, independent art and design professors ranked drawings produced with AIfred better in 33 of 36 cases. Our findings indicate that spatially co-located AI assistance benefits tasks whose guidance shares a spatial frame with the work.

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Gregorio Orlando, Milan Groshev, Eduardo Castelló Ferrer. 2026-09-30. AIfred: Augmented Learning through Functional Robotic Embodiment at the Desk. https://arxiv.org/abs/2609.38737

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