CARE’s assessment tools let instructors and researchers define the rubrics and criteria they want to use, then apply those rubrics directly alongside the student’s work. The text or PDF appears on one side, and the rubric with scoring fields and comment boxes appears on the other, so reviewers can assign points and write feedback criterion by criterion while seeing the relevant passage at the same time. This keeps assessment structured, transparent, and easy to follow for both teachers and learners.
One can integrate NLP models into CARE’s assessment tools. In studies that involve grading or structured feedback, you can configure the NLP integration to pre‑assess submissions based on your rubric. The system pre‑fills scores, short justifications, and feedback text for each criterion, so assessors start from a consistent baseline instead of a blank form. Instructors and reviewers stay in control of the final assessment. They review the LLM suggestions directly in CARE’s assessment interface, adjust scores and wording where needed, and finalize the result. This integration helps you scale grading and feedback in large courses while maintaining human control.