We are conducting a research study with education professionals and experienced practitioners. The goal is to collect real-world tutoring and academic scenarios that will help train AI models to handle complex educational advisory situations. The research objective is to help AI understand real education situations, including prerequisite gaps, learning style mismatches, and the hidden details that change how a student needs to be taught. Tool use is required for this study; submissions describing purely conversational scenarios will be rejected. Your story must reflect real education expertise and knowledge of how learning and teaching actually work. Submissions accompanied by real evidence (e.g., assignment sheets, rubrics, student work, lecture notes, syllabi, scheduling tools) are significantly more likely to be approved. Approval criteria include coherent fields and story, real subject-specific educational detail, at least 3 concrete learning constraints, and a clear hidden fact that changes the tutoring approach.
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