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Calibrating Exams Using
3 Different Parameters:

As soon as our platform grows we will use 3 different parameters for an optimal choice of question for your students


DIFFICULTY

difficulty

It is a well known fact that newly created MCQ questions can be extremely hard for students to answer and this often results in very low pass rates upon the first usage of new questions in the exams.

Only after students repeat the exam a few times, can they actually gather the questions they remember and this results in somewhat better pass rates. Difficulty parameter is also to be used carefully with relevance-meter.


Our difficulty-meter aims to better optimize the question difficulty for first time exam takers to elimiate this issue.

recency

Recency

Another issue with MCQ questions is that students oftenrecall and summarizethe questions they can remeber from the previous exams. This results in very high pass rates upon repeated usage of older questions.

Our recency-parameter ensures that students cannot easily pass the exams by simply recalling and writing down the questions from previous exams. Of course this parameter should be used in moderation along with the difficulty-meter.


Our recency-parameter aims to constantly provide students with new questions, these questions however should not be too hard and irrelevant.

relevance

relevance

Not a common issue with MCQ type of questions is a lack of relevance to the topics taught in your classes. However, if the questions are found somewhere ready-to-use online, then questions can often be completely irrelevant.

Our questions are tagged by keywords the students should know definitions and relations of, in order to successfully answer a questions. While this can narrow down the choice of questions,it is recommended to check the questions personally before finally giving them to the students.

Our relevance parameter aims to provide your students with relevant questions. Questions should however stick to general student-grade topics.

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AI System Prompt

Edit this prompt to customize question generation for this session. This will override once refreshed.

Choose the difficulty level for the questions to be generated.

Runs the separate AI relevance/difficulty scoring request right after generation.

Leaves each question's explanation blank instead of having the AI write one.

Generates higher quality distractors.

LLMs are known to make the correct answer obviously long. Check this box to fix it.

The system message is sent as part of the user message instead of as a separate system message.

Sends ONLY your text from the "AI System Prompt" box above + the file text. The built-in guidelines, the system message and the "Generate EXACTLY N questions" line are left out. The JSON format instructions are a separate option: "Request Json Format".

Asks the model to answer in JSON: sends the JSON format instructions with the JSON example, "Always respond with valid JSON only" and JSON mode (response_format). Untick it if your own prompt asks for a different answer format.

Does not force JSON mode in the request, so the model can answer like "Frage 1: … (A)–(E) … Antwort: B" or "Question 1: … (A)–(E) … Answer: B". An answer that is not JSON is always tried in this text format as well; if it is neither, you get the error "Invalid LLM response format".

Builds a knowledge graph from your text first, then generates questions from it. Produces more rigorously-grounded distractors. Uses significantly more API calls/time.

Controls which entity types are allowed to be the subject of a generated question - not what gets read from your document (every document is always read in full either way).

Select at least one domain.

Sends only your uploaded file + the prompt above to DeepSeek as a single user message (no system message), with thinking enabled at DeepSeek's default effort. Nothing else is added: no difficulty block, no format instructions, no other settings. Turns off every other option and pipeline (including the Knowledge Graph).

8K64K128K384K

Unchecked: max_tokens is not sent at all, so DeepSeek's own default applies.

How many times to send this same request. Every call is a separate, independent request (DeepSeek keeps no memory between calls). For every call 4 files are downloaded: request NN.txt, request NN.json, response NN.txt, response NN.json. With more than 1 call no questions are created - it is a documentation run.

Leave empty to use admin default.

8K64K128K384K (override)

Left as-is: uses the site default (8,000 tokens, non-thinking).


Leave blank for the default (100). Entering a number here turns off Questions Per Page.

Leave blank to generate 15 questions from the .txt file.

Processing PDF...

Starting…

8K64K128K384K (override)

Generated Questions

Sends one extra, separate AI request to rate each question's relevance to the source PDF and its difficulty - optional, only runs when you click this.

Custom Questions

Add your own questions manually to supplement the generated ones.

Create Exam

Enter multiple email addresses separated by commas or new lines

⬇ Export JSON ⬇ Export Moodle XML
“Life is like a multiple choice question, sometimes the choices confuse you, not the question itself.“

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