Drawing Your Programs: Exploring the Applications of Visual-Prompting with GenAI for Teaching and Assessment

Fuente: arXiv
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Main Authors: Smith IV, David H., Monisha, S. Moonwara A., Vadaparty, Annapurna, Porter, Leo, Zingaro, Daniel
Format: Preprint
Published: 2026
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author Smith IV, David H.
Monisha, S. Moonwara A.
Vadaparty, Annapurna
Porter, Leo
Zingaro, Daniel
author_facet Smith IV, David H.
Monisha, S. Moonwara A.
Vadaparty, Annapurna
Porter, Leo
Zingaro, Daniel
contents When designing a program, both novice programmers and seasoned developers alike often sketch out -- or, perhaps more famously, whiteboard -- their ideas. Yet despite the introduction of natively multimodal Generative AI models, work on Human-GenAI collaborative coding has remained overwhelmingly focused on textual prompts -- largely ignoring the visual and spatial representations that programmers naturally use to reason about and communicate their designs. In this proposal and position paper, we argue and provide tentative evidence that this text-centric focus overlooks other forms of prompting GenAI models, such as problem decomposition diagrams functioning as prompts for code generation in their own right enabling new types of programming activities and assessments. To support this position, we present findings from a large introductory Python programming course, where students constructed decomposition diagrams that were used to prompt GPT-4.1 for code generation. We demonstrate that current models are very successful in their ability to generate code from student-constructed diagrams. We conclude by exploring the implications of embracing multimodal prompting for computing education, particularly in the context of assessment.
format Preprint
id arxiv_https___arxiv_org_abs_2602_10529
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Drawing Your Programs: Exploring the Applications of Visual-Prompting with GenAI for Teaching and Assessment
Smith IV, David H.
Monisha, S. Moonwara A.
Vadaparty, Annapurna
Porter, Leo
Zingaro, Daniel
Computers and Society
When designing a program, both novice programmers and seasoned developers alike often sketch out -- or, perhaps more famously, whiteboard -- their ideas. Yet despite the introduction of natively multimodal Generative AI models, work on Human-GenAI collaborative coding has remained overwhelmingly focused on textual prompts -- largely ignoring the visual and spatial representations that programmers naturally use to reason about and communicate their designs. In this proposal and position paper, we argue and provide tentative evidence that this text-centric focus overlooks other forms of prompting GenAI models, such as problem decomposition diagrams functioning as prompts for code generation in their own right enabling new types of programming activities and assessments. To support this position, we present findings from a large introductory Python programming course, where students constructed decomposition diagrams that were used to prompt GPT-4.1 for code generation. We demonstrate that current models are very successful in their ability to generate code from student-constructed diagrams. We conclude by exploring the implications of embracing multimodal prompting for computing education, particularly in the context of assessment.
title Drawing Your Programs: Exploring the Applications of Visual-Prompting with GenAI for Teaching and Assessment
topic Computers and Society
url https://arxiv.org/abs/2602.10529