How I Built a Document-to-Quiz Parser: Turning Messy Word, PDF, and Google Docs into Structured Question Banks

说明与用途

ExamParser 将混乱的 Word、PDF 和 Google Docs 转换为 Canvas 可用的测验，自动推断结构并输出 QTI 1.2。

问题

Converting unstructured Word, PDF, and Google Docs into Canvas‑ready quizzes requires inferring questions, types, and answers from layout and styling, not just parsing text.

结果

ExamParser transforms messy documents into structured question banks, reducing manual effort and improving consistency for Canvas imports.

工作流

• Extract blocks with text, style, coordinates, and list status from DOCX, PDF, or Google Docs
• Normalize blocks into a common schema
• Segment blocks into questions using a tolerant regex for numbering
• Classify each question as MCQ, True/False, Cloze, Matching, or Short Answer based on markers
• Extract correct answer(s) by detecting annotations such as asterisks, bold, or "Ans:"
• Emit QTI 1.2 ZIP or Excel/CSV for migration

证据

ExamParser … drop in a Word, PDF, or Google Doc and get a Canvas‑ready quiz out.

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The single most important design decision: one normalizer, many extractors.

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Returning None instead of guessing is the discipline that keeps the tool trustworthy.

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