Reading the same lecture notes again can make a topic feel familiar. A blank page shows whether you can explain it. The useful next step is a set of questions that makes you retrieve the idea, apply it, and check your answer against the material you were taught.
OGAD (Off Grid AI Desktop) can help turn saved lecture notes into practice questions using a model on your computer. Download the app and model first, prepare your local files, and test the workflow offline. Once those resources are ready, you can generate and answer questions without an internet connection.
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What do you need before studying offline?
You need a downloaded local chat model and lecture notes saved on the computer. Text and Markdown files are simple choices. Text-based PDFs and DOCX files can also supply extracted text. Scanned pages may need a separate text conversion first; a file attachment does not guarantee readable text from a scan.
Use material you are allowed to use. Remove classmates' personal details from shared notes. Keep the course's learning objectives beside the notes so you can check the questions against the intended topic.
This workflow uses core chat and file features. It does not need background screen recording. Choose a local model rather than a remote endpoint for the offline session. Complete any model and document-search resource downloads before disconnecting. The desktop file processing implementation shows how attachments become content for chat.
How do you add a lecture to the chat?
Open a chat, use + > Attach files, and select your notes. Wait for processing and inspect the extracted text where shown. Check a heading and an important paragraph against the original. If a formula, table, or diagram became unreadable, provide a checked text explanation before asking for questions about it.
For a longer course, create a project through Projects > New project. Give it a clear name. Open Knowledge & settings > Knowledge base > Add files, add the relevant notes, and wait for indexing. Start the session through Chats > New chat in that project.
Project chat retrieves relevant passages automatically. It does not read every page into every answer. Use one lecture or a small set of related files per exercise. In a reused project, avoid unrelated chats and sources that could blur the topic. The project chat implementation retrieves a bounded set of passages and can include recent chats from that project.
Before a library trip or commute, disconnect the computer and try one question. Confirm the local model and source files still work.
How do you ask for questions that test understanding?
Tell the model what the lecture covers, which question types you want, and what it must do when the notes do not support an answer. Avoid starting with “Make 100 questions.” A small mixed set is easier to inspect and correct.
Suppose you are revising a lecture on database transactions. Your notes explain atomicity, isolation, and a booking example. They do not discuss every database engine. A useful first request is:
Use only the attached transaction lecture notes. Make eight practice questions: three short recall questions, three application questions using small examples, and two questions that ask me to explain a distinction. Stay within the notes. Do not assume facts about a specific database engine. Return the questions first. Put the answer key in a separate section, with the source heading and a short supporting excerpt for each answer. Flag anything the notes do not explain clearly.
Check each source excerpt and answer before you rely on the key.
Which question types should you keep?
Keep questions that test different things. Several questions that ask for the same definition create the appearance of coverage without much extra practice.
| Question type | What it helps you practise | What to check |
|---|---|---|
| Recall | State a term or rule from memory | The expected answer is in the notes |
| Explain | Describe why an idea works | The explanation has enough source support |
| Apply | Use an idea in a new small example | The example has all necessary information |
| Compare | Separate two related concepts | The distinction matches the course material |
| Find the error | Correct a flawed explanation | There is a clear, supported error |
For the transaction lecture, “Define atomicity” is a recall question. “A booking changes two records but stops after the first update; what property is at issue?” asks you to apply the idea. Check that the scenario is unambiguous before adding it to your set.
How do you check the answer key?
Review the key while making the set, then move it out of sight for practice. Save the questions and the checked key as separate local documents if that helps. OGAD can draft the text; you control how you save and organise it.
For each question, ask:
- Does the question have enough context to answer?
- Does the source support every required point?
- Could another reasonable answer also be correct?
- Has the model introduced terminology the lecture did not teach?
- Does the answer depend on an unreadable formula or missing diagram?
Rewrite or remove weak questions. If the lecture notes are incomplete, mark the item for a tutor or another approved source. More confident wording will not fill that gap.
Avoid treating generated questions as predictions of the real exam. They are practice material based on the files you supplied.
How do you use the questions to find weak topics?
Attempt the questions before viewing the key. Write enough of an answer to expose your reasoning. Then compare your response with the checked source, not only with the model's score.
You can ask for targeted feedback:
Compare my answer with the attached lecture notes and the checked answer key below. Identify correct points, missing points, and unsupported statements. Quote the relevant source passage. If the notes do not settle a point, say so. Suggest one follow-up question for the main gap.
Keep a small revision log: question, missing idea, corrected explanation, and source heading. For the booking example, the gap might be confusing an incomplete transaction with two transactions interfering. The next exercise should target that distinction.
When you return, answer a revised example before reading your old response.
What if the questions are repetitive or too difficult?
Narrow the request. Name one source section, ask for fewer questions, and specify the level of reasoning expected. If the answers use facts outside the course, require source support and remove unsupported items.
For long notes, split the work by lecture or learning objective. Maintain a manual coverage list so you can see which topics still need questions. Retrieval can help find passages; it cannot prove that the entire syllabus has been tested.
If file processing fails, inspect the source text. If the chat stops working offline, check that a local model is selected and all required resources finished downloading. A remote model still needs a network connection.
Make one useful practice set today
Download Off Grid AI Desktop, add one lecture, and make eight questions with a source-backed answer key. Check the set, hide the answers, and attempt it. Use the first clear gap to choose your next revision task.
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