Using machine learning to generate good spaced repetition prompts from explanatory text

A challenging research problem. Some notes:

• GPT-4 can often generate usable spaced repetition prompts for declarative knowledge from explanatory text with guidance
  • In prompt generation, choosing reinforcement targets and writing prompts for those targets are two separate problems
  • Framing prompt generation as a filtering problem on reinforcement targets
  • In prompt generation, LLMs may perform better when given prompt-writing principles
  • In prompt generation, LLMs often need extra hints about what angle to reinforce
  • In prompt generation, LLMs may perform better with ample context
• In prompt generation, LLMs lack prompt-writing patterns for complex conceptual material
• Some simpler subtasks which LLMs can accomplish:
  • GPT-3 can generate shallow variations of spaced repetition prompt questions
  • GPT-3 can transform cloze deletion prompts into question-answer prompts
  • GPT-4 can probably estimate whether two flashcards are functionally equivalent
  • GPT-4 can probably estimate whether one prompt will spoil retrieval of another
• A dataset of expert-written prompts would help development of prompt generation systems

Other attempts

• http://autonki.com from Sunny Chen at OpenAI
• Polar and Sana Labs use the OpenAI GPT-3 API
  • Sana Labs fine-tunes GPT-3 using known-good content/question/answer data
• Ozzie Kirkby did some experiments with iarfmoose/t5-base-question-generator · Hugging Face, which is a fine-tuned T5 model.
• Aithal, S. G., Rao, A. B., & Singh, S. (2021). Automatic question-answer pairs generation and question similarity mechanism in question answering system. Applied Intelligence. use ProphetNet (fine-tuned on SQuAD) to generate questions from passages and BERT to answer those questions
• Steuer, T., Filighera, A., Meuser, T., & Rensing, C. (2021). I Do Not Understand What I Cannot Define: Automatic Question Generation With Pedagogically-Driven Content Selection. ArXiv.
  • a BERT-based model with a separate content selection mechanism
  • helpful bibliography
• https://www.r-bloggers.com/2024/01/comparing-gpt-4-3-5-and-some-offline-local-llms-at-the-task-of-generating-flashcards-for-spaced-repetition-e-g-anki/
  • Simplistic prompt design but some methodical evaluation design

    Reading queue

• A systematic review: Kurdi, G., Leo, J., Parsia, B., Sattler, U., & Al-Emari, S. (2020). A Systematic Review of Automatic Question Generation for Educational Purposes. International Journal of Artificial Intelligence in Education, 30(1), 121–204. https://doi.org/10.1007/s40593-019-00186-y

Graveyard

• [[Log: experimenting with GPT-3 to generate spaced repetition prompts]]