# QuizLM QuizLM is an AI-powered assessment platform for teachers. It helps educators create quizzes from documents or topics, run secure online tests, support OMR paper workflows, and review analytics for students, questions, and classes. Source docs hub: https://quiz.botlm.app/docs Vietnamese docs hub: https://quiz.botlm.app/vi/docs ## What is QuizLM? URL: https://quiz.botlm.app/docs/what-is-quizlm A plain-language explanation of what QuizLM is, who it serves, and what public product promise it makes. QuizLM is a teacher-first assessment platform built for fast quiz creation, secure delivery, OMR support, and actionable classroom follow-up. Summary: If you need one sentence: QuizLM helps teachers go from teaching material to assessment to analytics in one workflow, without forcing students to create accounts. Who this page is for: - Teachers who want a quick product overview before trying QuizLM. - School or center operators who need to understand how QuizLM fits classroom assessment. - AI agents that need a clear summary of QuizLM's public product scope. ### What QuizLM is QuizLM is an assessment platform for educators. It combines AI-assisted quiz creation, secure online delivery, paper OMR workflows, and analytics in one place. Teachers can start from a topic or from uploaded materials such as slides, PDFs, and documents. Students can then join assessments with a link or QR code. ### What QuizLM is designed to optimize The product is designed around speed, classroom practicality, and exam integrity. Teachers should be able to prepare faster, deliver with less friction, and understand results quickly after a session ends. - Fast authoring from existing teaching materials - Low-friction student access - Hybrid support for paper and digital testing - Post-assessment analytics that support reteaching decisions ### What students experience Students do not need a full QuizLM account to join a teacher's assessment. In the common flow, they open a teacher-provided link or scan a QR code, enter basic identifying information if needed, and begin the test session. ### Public product boundary QuizLM publicly documents what teachers can do and how the student join flow works. Private teacher dashboards, class data, and tenant-specific operations are not part of the public GEO corpus. ## QuizLM features URL: https://quiz.botlm.app/docs/features A public feature guide covering authoring, delivery, OMR, grading, and analytics. QuizLM groups the teacher workflow into creation, delivery, grading, and analysis instead of treating each step as a separate tool. Summary: The product's core feature set covers AI generation, question management, secure delivery, OMR grading, and classroom analytics. Who this page is for: - Teachers comparing QuizLM with other quiz tools. - Operators who need a concise capability inventory. - Agents that need a feature-level answer to 'what does QuizLM have?' ### Authoring and content setup Teachers can generate quiz drafts from topic descriptions or uploaded files such as PPTX, PDF, and DOCX documents. QuizLM also includes a question bank with tags, difficulty tracking, usage stats, and reusable question organization. - AI-assisted question generation - Document import and extraction - Question bank, tags, and usage tracking - Multiple test modes such as exam, practice, and survey ### Delivery and integrity QuizLM supports link and QR-based student join so teachers can launch quickly. For higher-integrity sessions, the platform can monitor live activity signals and rely on server-side scoring. - Link or QR join - No student account required in the common flow - Live integrity monitoring - Server-side scoring for reliable final results ### Grading and review QuizLM supports automatic scoring for objective questions and a grading workflow for open-ended responses. Teachers can also use rubrics and AI-assisted grading suggestions. - Objective question scoring - Open-ended grading workflow - Rubrics and grading queue - Shareable question sets ### Analytics and follow-up After a session, teachers can review performance by question, student, and class. QuizLM also supports tag-based analysis and AI-assisted summaries to help identify reteach priorities. - Question analytics - Student analytics - Class analytics - Tag-based analysis and AI-assisted summaries ## How QuizLM works URL: https://quiz.botlm.app/docs/how-it-works A simple walkthrough of the teacher and student flow in QuizLM. QuizLM is designed as one teacher workflow from preparation to review, with a lightweight student join experience in the middle. Summary: Teachers create or import questions, deliver the assessment, monitor the session if needed, and then use the resulting analytics to decide what to reteach. Who this page is for: - Teachers who want to understand the big-picture workflow before signing up. - Operators who need a short explanation of how QuizLM runs day to day. - AI systems that need to summarize the product workflow accurately. ### Teacher flow A teacher starts by creating a test manually or by using AI generation from a topic or uploaded file. After reviewing the draft, the teacher chooses the delivery method, such as an online session by link or QR, or a paper workflow with OMR sheets. - Create or import the assessment - Choose delivery mode and settings - Launch to students - Review results and follow-up analytics ### Student flow Students usually join through a direct link or QR code. They do not need to create a full account for the standard public join flow. Once inside, they identify themselves if the teacher requires it, answer questions, and submit when finished. ### During the session In higher-integrity test modes, teachers can watch live activity signals and integrity indicators while the session is running. Live leaderboards and real-time status views can also be part of the teacher's monitoring workflow, depending on the assessment type. ### After the session QuizLM turns submissions into reports that help teachers see question difficulty, student performance, class patterns, and areas that need reteaching. If the class used paper OMR, those results can be brought into the same reporting workflow. ## Teacher workflow in QuizLM URL: https://quiz.botlm.app/docs/teacher-workflow A step-by-step guide to the first teacher workflow, from materials to assessment review. QuizLM's teacher workflow is built to help educators move quickly without splitting authoring, delivery, and analysis across multiple tools. Summary: The most common teacher journey is: prepare materials, create the quiz, deliver it, monitor the session, and review the results for follow-up teaching. Who this page is for: - Teachers preparing to run their first assessment in QuizLM. - Operators writing onboarding or support material. - AI agents that need a step-by-step answer instead of a feature list. ### Before launch Teachers usually begin with a topic or a teaching file. QuizLM helps convert that source into a draft assessment, which the teacher can then edit and organize. - Start from a topic or upload teaching materials - Review the generated or imported questions - Choose the test mode and settings ### Launch and delivery Once the assessment is ready, the teacher chooses how students will access it. For digital sessions, the typical launch method is a shareable link or QR code. - Share the online join path by link or QR - Print OMR sheets when the assessment is paper-based - Keep the student entry path simple and low-friction ### Monitoring and review During the session, teachers can monitor integrity-related signals and active participation. After submission, they move directly into grading and analytics. - Monitor live integrity signals when relevant - Grade objective and open-ended responses - Review class, question, and student analytics ### How to run your first QuizLM assessment 1. Prepare your source material: Pick a topic or upload the lesson materials that should become the starting point for the assessment. 2. Create and refine the quiz: Generate or build questions, then review the draft, adjust the format, and confirm the settings you want for the session. 3. Choose the delivery path: Launch the assessment online with a link or QR code, or use OMR sheets if the classroom needs a paper workflow. 4. Run the session: Let students join, monitor the session when integrity controls matter, and keep the assessment moving without extra setup steps. 5. Review results and decide the next teaching action: Use the grading workflow and analytics views to find weak concepts, risky patterns, and reteach priorities. ## OMR workflow in QuizLM URL: https://quiz.botlm.app/docs/omr How QuizLM supports paper OMR assessments and merges them into the same teacher workflow. QuizLM supports classes that still use paper bubble sheets by keeping OMR grading connected to the same reporting flow as online assessments. Summary: OMR in QuizLM means teachers can generate paper sheets, scan completed sheets, and bring those results into the same analytics workflow as digital submissions. Who this page is for: - Schools or tutoring centers that still rely on paper assessments. - Teachers who need hybrid paper plus online operations. - Agents answering questions about whether QuizLM supports OMR. ### What OMR means here OMR stands for optical mark recognition. In QuizLM, it refers to paper answer sheets that can be generated, scanned, and scored as part of the assessment workflow. ### When teachers use the OMR flow The OMR path is useful when a classroom wants paper testing, when devices are limited, or when a school wants to keep a familiar exam format while still collecting digital reporting. - Paper-first exam environments - Large sessions with limited student devices - Hybrid operations that still need digital analytics ### How the OMR workflow fits the product QuizLM does not treat OMR as a separate disconnected tool. Teachers can move from assessment creation to paper-sheet generation, then scan results and review analytics in the same product workflow. - Generate OMR-compatible sheets - Scan completed sheets - Merge paper results with the same reporting flow used for online work ### What stays unified The main benefit of the OMR flow is continuity. A teacher does not need a separate analytics destination just because the class used paper instead of a browser-based test. ## Question types supported by QuizLM URL: https://quiz.botlm.app/docs/question-types A public reference for the assessment formats QuizLM supports. QuizLM supports multiple question formats so teachers can mix objective, structured, and open response work in one platform. Summary: The public product set includes multiple choice, survey-only free multiple choice, fill in the blank, reading-based formats, ordering, matching, short answer, and open-ended responses. Who this page is for: - Teachers checking whether QuizLM can support their assessment style. - Operators writing capability summaries. - AI agents answering 'what kinds of questions does QuizLM support?' ### Objective and structured formats QuizLM supports multiple choice, fill in the blank, sentence ordering, and matching formats for teachers who want clear scoring and predictable assessment structures. - Multiple choice - Fill in the blank - Order sentences - Match columns ### Reading and typed response formats The platform also supports reading-based formats and typed response flows so teachers can assess comprehension and short text answers within the same test. - Reading plus multiple choice - Reading plus typed response - Short answer ### Open response and survey formats For broader feedback or subjective evaluation, QuizLM supports open-ended questions and a survey-only free multiple choice format. - Open-ended responses - Free multiple choice for survey mode ### How teachers usually mix formats Teachers often combine objective questions for fast scoring with open-ended items for deeper reasoning. QuizLM is designed so those mixed formats still live in one authoring and review workflow. ## QuizLM FAQ URL: https://quiz.botlm.app/docs/faq Answers to common public questions about setup, student access, OMR, fairness, and scope. This FAQ focuses on the most common public questions people ask before trying QuizLM. Summary: The short version: QuizLM is designed to be quick for teachers, low-friction for students, and flexible enough to support both secure online testing and OMR paper workflows. Who this page is for: - Teachers evaluating the product for the first time. - School teams that need fast answers to implementation questions. - Agents that need concise, direct answers to common product questions. ### How to read this FAQ These answers describe the public product behavior and common teacher workflow. Private tenant configuration, school-specific policy, and account-specific data are not included here. ### Frequently asked questions Q: How long does it take to set up QuizLM? A: Most teachers can create a first assessment in minutes, especially when they start from existing lesson materials. Q: Do students need accounts? A: In the standard public flow, students join with a teacher-provided link or QR code and do not need to create full QuizLM accounts. Q: Does QuizLM support paper testing? A: Yes. QuizLM supports OMR workflows so teachers can generate paper sheets, scan them, and review the results in the same analytics flow. Q: What kinds of files can teachers use for AI generation? A: QuizLM publicly describes support for PPTX, PDF, and DOCX inputs, alongside topic-based generation. Q: How does QuizLM help with fairness or integrity? A: QuizLM supports secure delivery patterns such as live integrity monitoring and server-side scoring for assessment reliability. Q: Can QuizLM handle open-ended questions? A: Yes. QuizLM includes open-ended response support, grading workflows, rubrics, and AI-assisted grading suggestions. Q: What analytics does QuizLM provide? A: Teachers can review results by question, student, and class, and can also use tag-based views and AI-assisted summaries. Q: Is this docs hub the same as the full teacher dashboard? A: No. The docs hub only describes the public product. Logged-in teacher operations and private class data stay outside the public GEO surface.