Auto-Generating Analytic Rubrics for Criteria-Oriented High-Information Feedback

Developing analytic rubrics requires considerable preparation time for teachers, highlighting the necessity for adequate support mechanisms. This paper presents and evaluates a teacher-support tool designed to automate the generation of analytic rubrics for assessing student submissions and delivering actionable feedback. The tool incorporates a large language model as a core component, employing generalized prompt templates to enhance its versatility. The generated outputs are systematically compared against predefined teacher expectations to evaluate the tool's applicability and effectiveness in three real-world educational scenarios.