Prompt Machine: Enabling Physical LLM-Interactions for Learning

As generative AI technologies enter school settings, educators face uncertainty around how to meaningfully integrate these tools into teaching and learning. We present Prompt Machine, a tangible learning tool designed to support AI literacy, scaffold curriculum-aligned writing activities, and spark critical reflection on the role of AI in education. Informed by interviews with secondary school teachers and grounded in theoretical design considerations, Prompt Machine enables learners to input text, modify it using a physical prompt language, and receive AI-generated rewritings in tangible form. This demo showcases how physical interaction and collaborative exploration can make AI technologies more accessible, explainable, and reflective in classroom contexts. In line with DIS 2025’s theme of Designing for a Sustainable Ocean, this demo features customised tangible blocks and example texts centred on ocean sustainability, inviting conference participants to engage in hands-on exploration and dialogue around AI and environmental themes.

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Publication Details

Published
2025-07-05
DOI
https://doi.org/10.1145/3715668.3735602
Primary Topic
Semantic Web and Ontologies
Type
article
Field-Weighted Citation Impact
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article

Prompt Machine: Enabling Physical LLM-Interactions for Learning

Martin Lindrup, Niels van Berkel, Rune Møberg Jacobsen, Peter Axel Nielsen et al.
Semantic Web and Ontologies
article

Prompt Machine: Enabling Physical LLM-Interactions for Learning

Martin Lindrup, Niels van Berkel, Rune Møberg Jacobsen, Peter Axel Nielsen, Dimitrios Raptis, Joel Wester
article en

Abstract

As generative AI technologies enter school settings, educators face uncertainty around how to meaningfully integrate these tools into teaching and learning. We present Prompt Machine, a tangible learning tool designed to support AI literacy, scaffold curriculum-aligned writing activities, and spark critical reflection on the role of AI in education. Informed by interviews with secondary school teachers and grounded in theoretical design considerations, Prompt Machine enables learners to input text, modify it using a physical prompt language, and receive AI-generated rewritings in tangible form. This demo showcases how physical interaction and collaborative exploration can make AI technologies more accessible, explainable, and reflective in classroom contexts. In line with DIS 2025’s theme of Designing for a Sustainable Ocean, this demo features customised tangible blocks and example texts centred on ocean sustainability, inviting conference participants to engage in hands-on exploration and dialogue around AI and environmental themes.

Aalborg University (DK)
Openalex Percentile: Top 92%
Semantic Web and Ontologies
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Prompt Machine: Enabling Physical LLM-Interactions for Learning — Martin Lindrup, Niels van Berkel, et al. · (2025) | TGRS Research Map | TGRS