Ace
Short answer: build every question from your own lecture material, not from general knowledge; tie each answer to the exact line in your slides or notes that proves it; make the wrong options believable but clearly wrong according to that source; and check the answer every time you practise. A quiz with one wrong answer in it is worse than no quiz, because testing makes whatever you answer stick, mistakes included.
Why turn your lectures into a quiz at all?
Because answering questions is the most reliable way to remember what a lecture said. In Roediger and Karpicke's (2006) classic study, students who practised recalling a passage remembered far more a week later than students who reread it, even though the rereaders felt more confident. Dunlosky and colleagues' (2013) large review of study techniques rated practice testing as one of only two high-utility methods.
Lectures are the ideal source for those questions. Your lecturer chose what to cover, used the terms the exam will use and usually set the exam too. A quiz built from the slides tests you on exactly what you'll be asked, in the words you'll be asked it. For more on why this works, see active recall vs rereading.
Why does a quiz need to be trustworthy?
Because testing strengthens whatever you answer, right or wrong. Roediger and Marsh (2005) found that taking a multiple-choice test boosted later recall, but students also sometimes picked up the wrong options as facts. Butler and Roediger (2008) then showed the fix: feedback after each answer increased correct recall and cut those errors. A quiz is only as good as its answer key, and the answer key is only as good as its link to the source.
This is where general AI tools get risky. In a study reported by Boston University in 2023, researchers asked ChatGPT to write questions for a medical school immunology course: only 19 of the 60 questions (32%) came out correct with correct explanations, and a quarter had wrong or misleading answers. Models have improved since, but the lesson holds: a fluent question is not the same as a correct one, and you can't spot the wrong ones if you don't know the topic yet. That's the whole reason you're quizzing yourself. Our guide on whether you can trust AI study answers goes deeper.
How do you turn a lecture into a quiz by hand?
- One slide, one or two questions. Go through the deck and turn each key point into a question. Headings make good prompts: "Glycolysis: net ATP" becomes "What is the net ATP yield of glycolysis?"
- Write the answer with its slide number. Every answer gets a reference, such as "slide 14". If you can't point at a line that proves it, the question doesn't go in.
- Mix the formats. Short answer for definitions, put-the-steps-in-order for processes, label-the-diagram for anatomy and structures, and multiple choice where the exam uses it.
- Make wrong options from real confusions. The best distractors are things students actually mix up: the neighbouring stage of a cycle, the drug from the same class, the case with the similar facts. Avoid options that are obviously silly.
- Ask what the lecturer stressed. If they spent ten minutes on something or said "this comes up every year", write three questions on it.
It works, but it's slow: writing good questions can take longer than the lecture itself, which is why most students never get round to it.
How do you use AI to make lecture quizzes without learning mistakes?
- Give it your material, not the topic. "Quiz me on the Krebs cycle" draws on general training data; "quiz me using only this lecture" anchors it to your course. Upload the slides or paste the notes.
- Demand a source line for every answer. Ask for the quote from your material that proves each answer. If it can't give one, delete the question.
- Spot-check against the slides. Check at least the first ten answers yourself. If any is wrong, check them all.
- Watch for drift. Answers that use terms your lecturer never used, or numbers that aren't in your notes, came from somewhere else. Your course's version is the one that's marked.
- Keep feedback on. Whatever tool you use, see the right answer and why after every question, not just a score at the end.
See how to get ChatGPT to quiz you for prompts that follow these rules.
How should you use your lecture quiz?
- Quiz first, reread second. Start a session with the questions, then reread only what you got wrong.
- Space it. Come back to each lecture's quiz a day later, then a week later. Spreading practice out beats cramming it (Cepeda and colleagues, 2006). See our spaced repetition schedule.
- Shuffle lectures together. Near the exam, mix questions from several lectures so you have to recognise which topic each question is about. See interleaving.
- Quiz a friend. Taking turns on the same questions turns arguing about wrong answers into learning.
This is what Ace is built for. It turns your own lecture slides, PDFs, Word documents or YouTube lectures into practice questions written only from that material, checks every answer against it, drops questions that fail the check, and shows the sentence from your file that backs each answer. You pick the chapters, then play solo or duel a friend. See how it works.
Frequently asked questions
Can AI make a quiz from my lecture slides?
Yes, if you give it the slides themselves. The key is making it answer only from that material and showing you the line that proves each answer, so you can check it.
How many questions should I make per lecture?
Enough to cover every key point once or twice. For a typical lecture that often means one or two questions per important slide, with extra ones on whatever the lecturer stressed.
Is multiple choice good for revision?
It works well, especially if your exam uses it, as long as you get feedback after each answer. Mix in short-answer and ordering questions so you also practise recalling without options.
What if a quiz answer disagrees with my lecture?
Go with your lecture. Your course's version is the one that's marked, so fix or delete the question.
Sources
- Roediger, H. L. & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255. PDF
- Roediger, H. L. & Marsh, E. J. (2005). The positive and negative consequences of multiple-choice testing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(5), 1155–1159. Record
- Butler, A. C. & Roediger, H. L. (2008). Feedback enhances the positive effects and reduces the negative effects of multiple-choice testing. Memory & Cognition, 36(3), 604–616. PDF
- Boston University Chobanian & Avedisian School of Medicine (2023, December 20). Study finds AI language model failed to produce appropriate questions, answers for medical school exam (study in Academic Pathology). bumc.bu.edu
- Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J. & Willingham, D. T. (2013). Improving students' learning with effective learning techniques. Psychological Science in the Public Interest, 14(1), 4–58. APS summary
- Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T. & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354–380. PubMed
