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

Описание и применение

ExamParser преобразует Word, PDF и Google Docs в готовые к Canvas викторины, автоматически определяя вопросы, типы и ответы.

Задача

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.

Результат

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

Рабочий процесс

• 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

Доказательства

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

Источник

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

Источник

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

Источник