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Nearly all prior research on LLMs in computing education has used text input, yet voice-enabled interfaces are becoming common. This exploratory study investigated how introductory programming students interact with Prompt Problems — tasks requiring natural-language prompts to generate correct code — under free choice of text or voice (N = 919). For two of three problems, students who typed were more likely to succeed on the first attempt than those submitting unedited voice prompts; editing transcribed voice prompts before submission erased the gap. Most students tried and preferred text, though some used voice complementarily. Qualitative analysis revealed perceived roles, drawbacks, and advantages of each modality, with implications for multimodal tools and instructional design.

  • Modality matters for first-attempt success: Unedited voice prompts underperformed typed ones on two of three problems; editing transcribed voice closed the gap — extending Prompt Problems Nl Programming Mistakes.
  • Student preference for text: Despite voice availability, most students chose and preferred typing, relevant to Student Experience design.
  • Complementary use: Some students mixed modalities, suggesting non-preferential, context-dependent strategies tied to Prompt Based Programming Lesson practice.
  • Instructional design: Findings inform multimodal CS Education tooling and AI Literacy around prompt construction.
  • Scales Prompt Problems research: Large N (919) builds on the Programming ITS Prompt Problems line of work.
  • Connected Concepts

  • Student Experience
  • CS Education
  • AI Literacy
  • Connected Articles

  • Prompt Problems Nl Programming Mistakes
  • Prompt Based Programming Lesson
  • Programming ITS
  • Citation

    Riegel, K., Hua, Y. C., Denny, P., Pădurean, V.-A., & Leinonen, J. (2026). Say What? Examining Text and Voice Input Modalities for Prompt-Based Programming in Computing Education. arXiv:2607.05808.