AI Multiple Choice Assessment Generator
Mr. Singh is preparing a 20-question end-of-unit test on cellular respiration. He enters the topic into the generator, selects Mixed as the Bloom's level, and reviews the output. Each distractor is labelled with the misconception it targets ("students often confuse ATP synthesis location") so he knows the assessment is actually testing understanding, not just guessing.
The AI Assessment Generator is one of the AI generators of OpenEduCat Tools. It generates diagnostic assessments, not just lists of recall questions.
This page fills in a draft from a template. Copy prompt gives you the prompt for any AI chat.
How it works
From topic or learning goal to an assessment draft you can copy, in four steps.
Enter a topic and learning goal
The teacher types a topic and can add a learning goal. The template fills these in; it does not analyse any text.
Select Bloom's level and number of questions
The teacher chooses the Bloom's taxonomy level (from Remember to Evaluate) and the number of questions. They can also choose Mixed, then write, for example, 5 recall questions, 3 application questions, and 2 analysis questions. This controls the cognitive demand of the assessment without requiring the teacher to write questions at multiple levels manually.
Review and edit questions and distractors
The AI generates the questions with four answer choices each. The correct answer is marked and each distractor is labelled with the misconception it targets. The teacher reviews every question, edits any that are unclear, and approves the set.
Copy or download
Copy the approved assessment with its answer key or download it as a text file.
What sets this generator apart
Built to help you write diagnostic questions, not just quantity.
Bloom's level label
The teacher selects a cognitive level: Mixed, Remember, Understand, Apply, Analyse, or Evaluate. The AI generates questions that genuinely target the selected level, a Level 4 question requires students to break information into parts and identify relationships, not just recall facts.
Bad distractors are obviously wrong, students eliminate them without thinking. Good distractors represent plausible misconceptions that students actually hold.
Answer key generation
Every draft includes an answer key with blanks for the teacher to fill in. Teachers can distribute the answer key after the assessment or use it to run a whole-class debrief.
Assessment types teachers build
End-of-unit tests are the most common use case. A 20-30 question assessment covering everything in a 3-week unit can start from the draft's stems, with a mix of recall and higher-order questions.
Reading comprehension checks can start from the passage's topic, with the teacher writing 5-10 questions that test whether students understood what they read. Literature teachers use this for novel chapters. History teachers use it for primary source documents. Science teachers use it for research articles.
Exit tickets are 3-5 question formative checks generated from the day's lesson objective.
Diagnostic pre-assessments establish baseline knowledge before a unit begins. The teacher generates a set of questions targeting prerequisite knowledge and gives it on Day 1. The results show which students already have the foundation to accelerate and which students need more scaffolding before new content is introduced.
- No student accounts.
- No ads.
- Data-processing agreement on request.
What this page does here
This page builds a draft from a template on this device. Copy prompt gives you the prompt for any AI chat.
Questions teachers ask
What is Bloom's taxonomy and why does it matter for MCQ assessment?
Bloom's taxonomy describes six levels of cognitive complexity: Remember, Understand, Apply, Analyze, Evaluate, and Create. Most teacher-written multiple choice tests over-index on Level 1 (recall) questions because they are easiest to write. The AI can generate questions at the level you pick, from Remember to Evaluate (including Level 4 analysis questions that require students to examine cause-and-effect relationships), so assessments can test deeper learning, not just memorisation.
What makes a good distractor?
A good distractor is a plausible wrong answer that a student who has a specific misconception would choose. For a biology question about mitosis, a strong distractor might describe meiosis, which students often confuse with mitosis. A weak distractor is obviously wrong to any student who read the chapter. The AI generates distractors by drawing on documented misconceptions in the subject area and labels each one so the teacher understands what conceptual error it targets.
Can I generate assessments from my own uploaded content?
No. There is no upload and no box for your own text. The form takes a topic and a learning goal. To work from your own text, use Copy prompt, add the text in an AI chat, and check the questions it writes.
How do I export to my LMS?
There is no LMS export. Copy the questions or download them as a text file, then add them with your LMS quiz builder.
Can I build an assessment from the question bank without generating new questions?
No. There is no question bank here, and the tool saves nothing. Keep your downloaded files and copy questions from them into a new assessment yourself.
Is the generator useful for formative assessments as well as summative tests?
Yes. Teachers can use the generator to start short exit tickets at the end of each lesson, a quick formative check. The generator can give an exit ticket outline from the lesson's topic and learning goal.
Related tools
AI with your school's own student and course data is part of OpenEduCat.
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