From Word Document to SLS in Minutes — Building a DOCX-to-QTI Converter for Singapore Teachers

📅 April 2026 ✍️ Wee Loo Kang Lawrence & Low Jun Hua 🏫 Singapore Physics Educators

The Problem Every Teacher Knows

Every year, Singapore teachers invest enormous effort crafting high-quality examination papers in Microsoft Word — carefully worded MCQ stems, detailed mark schemes, physics diagrams painstakingly drawn or embedded. When it comes time to put these questions onto the national Student Learning Space (SLS) platform, teachers face a second, entirely manual job: re-typing every question, re-uploading every image, and re-entering every correct answer — one by one — into the SLS authoring interface.

For a 30-question Paper 1 alone, this can take two to three hours. Multiply that across a department sharing five or six papers per year, and a meaningful slice of teacher time disappears into administrative reformatting rather than pedagogy.

The Idea: Automate the Bridge Between Word and SLS

SLS supports the international QTI 2.1 (Question & Test Interoperability) standard for bulk question import. A QTI package is simply a ZIP file containing structured XML — a machine-readable description of every question, its options, its correct answer, and its associated images. If we could automatically translate a Word document into a valid QTI package, teachers could go from a finished exam paper to a fully loaded SLS quiz in minutes.

Low Jun Hua built the first Python prototype as a Flask web app. The approach: unzip the .docx file (Word documents are ZIP archives internally), parse the XML, detect question numbers, classify MCQ versus structured responses, extract embedded images, and write out conformant QTI XML. The converter was then extended, hardened, and re-implemented as a fully in-browser tool — no server, no sign-in, no file upload to a third party. Everything runs locally in the teacher's own browser using JavaScript and the JSZip library.

What the Converter Does

• Parses the Word XML to detect question numbers, stems, MCQ options (A/B/C/D), images (DrawingML and legacy VML), and tables.
• Reads the mark scheme automatically — upload the matching MS .docx and correct answers are injected into every QTI item's correctResponse field.
• Handles tricky layouts — nested tables, transposed option grids (A/B/C/D as column headers), image-only options, and physics diagrams embedded as option choices inside <simpleChoice> elements.
• Sorts questions correctly — SLS uses file position as the question number, so the converter deduplicates and sorts Q001→Q030 before writing assessment_test.xml.
• Provides a Review & Edit step — after parsing, every question appears as an editable card in the browser. Teachers can toggle MCQ/Essay, fix stem text, change the correct answer, and review images before exporting.
• Exports a ready-to-import ZIP that can be uploaded directly to SLS without any further editing.

Alignment to the MOE EdTech Masterplan 2030

The EdTech Masterplan 2030 sets out a vision of "Technology-transformed learning, to prepare students for a technology-transformed world." It organises its outcomes around four pillars — Students, Teachers, Schools, and System — and calls for teachers to become "technologically-adept, collaborative learning designers" who are pedagogically proficient, data-literate, and continuously experimenting with technology. Its first strategic thrust is to "empower students' learning through greater customisation and personalisation with EdTech." This converter directly supports those goals:

• Teachers pillar — reducing administrative burden EdTech 2030 — The masterplan calls for teachers to spend their energy on learning design, not clerical work. Converting a 30-question paper manually into SLS can take two to three hours; this tool does it in under a minute, freeing teachers to focus on pedagogy and feedback.
• Students pillar — greater personalisation through formative assessment EdTech 2030 — With prelim papers instantly available on SLS, teachers can assign them as digital formative tasks, gather real-time class-level data, and personalise follow-up — directly enabling the masterplan's thrust on customisation and personalisation.
• System pillar — networked EdTech ecosystem and content sharing EdTech 2030 — Years of carefully crafted exam papers — with diagrams, worked answers, and mark schemes — can be shared across departments and schools as SLS question sets, building the networked content ecosystem the masterplan envisions.
• Teachers pillar — data-literate, experimentative professionals EdTech 2030 — Teachers who migrate their paper questions into QTI gain direct experience with digital assessment metadata (correctResponse, item identifiers, scoring), building the data literacy the masterplan identifies as essential for the modern teacher.
• Schools pillar — accessible on WOG devices EdTech 2030 — The tool is hosted on the official moe.edu.sg domain, making it accessible from Whole-of-Government (WOG) school devices without installation or special permissions — supporting the masterplan's goal of digitally-equipped learning environments.

Lessons Learned Building It

Word documents are far messier than they appear. The same visual layout — a question number followed by four labelled options — can be represented in dozens of different XML structures depending on the Word version, the template used, and the author's habits. Some papers put every question in a table; others mix paragraphs and tables; some use A. B. C. D. as paragraph text, others embed them in nested table cells, others use a transposed grid where A/B/C/D are column headers and the options are images in the rows below.

The most important engineering decision was to never throw away ambiguous content. Instead of silently dropping unknown structures, the converter surfaces them in the Review & Edit panel so the teacher can make the final call. A question that cannot be auto-classified as MCQ shows up as Essay — one click on the badge toggles it to MCQ and reveals the option fields.

Running entirely in the browser was a deliberate choice for privacy and accessibility. Teachers' exam papers — often confidential before sitting — never leave their device. There is no account, no quota, no subscription. The tool works offline once the page is loaded.

What's Next

The current tool handles Physics prelim papers well. Future directions include better support for mathematical notation (MathML inside QTI), multi-part structured questions with sub-question scoring, and a question-bank view that lets teachers search and reuse individual items across papers. Contributions and feedback from the Singapore teacher community are very welcome via the GitHub repository.

This tool is free and open-source. It was built by Singapore physics educators, for Singapore educators. If it saves your department even one afternoon a year, it has done its job.