Codesigning Ripplet: an LLM-Assisted Assessment Authoring System Grounded in a Conceptual Model of Teachers' Workflows
Yuan Cui, Annabel Marie Goldman, Jovy Zhou, Xiaolin Liu, Clarissa M Shieh, Joshua Yao, Mia Lillian Cheng, Matthew Kay, Fumeng Yang
ACM Human Factors in Computing Systems (CHI) 2026
An example feature of Ripplet’s multilevel reusable edits with LLMs: A teacher manually edits a question, and the system infers why this change was made and creates a reusable edit command, which can be reapplied to questions in other assessments.
Abstract
Assessments are critical in education, but creating them can be difficult. To address this challenge in a grounded way, we partnered with 13 teachers in a seven-month codesign process. We developed a conceptual model that characterizes the iterative dual process where teachers develop assessments while simultaneously refining requirements. To enact this model in practice, we built Ripplet,\footnote{A demo video of the system is provided in supplemental materials.} a web-based tool with multilevel reusable interactions to support assessment authoring. The extended codesign revealed that Ripplet enabled teachers to create formative assessments they would not have otherwise made, shifted their practices from generation to curation, and helped them reflect more on assessment quality. In a user study with 15 additional teachers, compared to their current practices, teachers felt the results were more worth their effort and that assessment quality improved.