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Design Implications for Teacher-Configurable Generative AI Writing Tools: A Participatory Design Study with StoryBot

Year: 2026

Type: article

Abstract: As generative AI (GenAI) tools become accessible, their integration into K–12 writing presents opportunities and challenges. This study partnered with 21 primary school teachers in a participatory co-design process to develop StoryBot, a teacher-configurable GenAI story-authoring platform. Teachers identified instructional needs and learning outcomes that informed system features, including genre-specific writing scaffolds, configurable prompts, and constraints on full-text generation to preserve student voice. The platform positions educators as co-designers of AI behavior rather than passive users. We conducted a pilot writing workshop with 13 youth (ages 8–12) and a focus group with six educators to examine how the platform influenced students’ writing behaviors and classroom integration. Findings demonstrate the value of teacher co-design and configurable AI systems in aligning GenAI tools with pedagogical priorities and practices. We present design implications for teacher-configurable GenAI writing systems that support student agency, ethical safeguards, and instructional alignment in human–AI coauthoring environments.

Source: International Journal of Human-Computer Interaction

DOI: 10.1080/10447318.2026.2739766

Authors: Ariel Han, Shenshen Han, Zhenyao Cai, Joey Huang, Franceli Cibrian, Kylie Peppler

Institutions: Utah State University, University of California, Irvine, North Carolina State University, Chapman University, Irvine University

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

OpenAlex ID: W7204171367

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