AI question-paper generator aligned to VTU syllabi.
Kwilo generates examinable question papers from your syllabus with enforced unit coverage, Bloom's taxonomy distribution, and marks pattern — in the format your university requires.
How the generator works
Select a course, semester, and exam type (CIE-1, CIE-2, or SEE). Kwilo pulls the syllabus from your institutional content store and generates questions distributed across units per the VTU/AKTU blueprint. You set the Bloom's level distribution (e.g., 30% Remember, 40% Apply, 30% Analyse) and marks pattern (2+2+5 or 5+5+10). The generator returns a formatted paper with an answer key and per-question CO mapping. Faculty review, add, swap, or remove questions before finalising. The final paper is exported as a password-protected PDF.
For faculty and exam cells across VTU, AKTU, and AICTE-affiliated colleges
Setting a balanced question paper takes an experienced faculty member 2–4 hours: pulling the syllabus, ensuring unit coverage, varying cognitive levels, checking marks totals. New faculty and visiting lecturers often produce papers biased toward certain units or Bloom's levels. Kwilo enforces coverage mechanically so every paper meets the university blueprint regardless of who sets it. Exam cells can queue papers in a pipeline and release them to examiners on a schedule, reducing the risk of early leakage.
Supported syllabi and formats
Kwilo ships VTU 2021 scheme, VTU 2022 CBCS, AKTU 2019 and 2023 revision, JNTU-H, Anna University R2021, PES University, and 14 other syllabi for engineering programs. Non-engineering programs can upload a custom syllabus. The marks pattern for each university exam type is pre-configured and overridable. Output formats: VTU standard format, AKTU standard format, or plain format compatible with your institution's header template.
Usage at scale
Across Kwilo's institutional customers as of April 2025, 14,300 question papers have been generated for CIE and SEE across engineering and science subjects. Faculty reported a median generation time of 6 minutes from opening the tool to downloading the final PDF. Paper quality scores (faculty self-rating of Bloom's distribution and unit coverage) averaged 4.3 out of 5 for AI-assisted papers vs. 3.7 for papers set without the tool.
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