We are a team of researchers at the University of Maryland and Yale, and we recently developed KAR³L, a research project investigating AI-assisted learning with flashcards. We have a pre-print of our first research work here:
https://arxiv.org/abs/2402.12291 . We’ve now launched a new flashcard scheduler that uses model-generated mnemonic devices to help boost vocabulary learning:
https://karl.qanta.org/landing.
Currently, KAR³L has 750 unique vocabulary terms and we are looking for feedback on our generated mnemonic devices to help improve them. We are currently conducting a research study where participants can earn up to $50 for studying with KAR³L. Details can be found here:
From Feb 26th to May 26th, we will conduct our user study, where there are two ways for you to earn monetary compensation for studying with KAR³L:
https://docs.google.com/document/d/1Ecv ... jn2yxpjpre1.
Base Reward: Users who study 20+ flashcards a day from the GRE deck over 5 unique days will be entered into a raffle to win one of 50 $25 gift cards2.
Power User Reward: Users who give feedback on 75 or more mnemonic devices will be entered into a raffle to win one of 50 $25 gift cardsLet us know what you think, and we hope KAR³L can be useful to help you study for the GRE. Thanks!
For more background on us,
Nishant:
https://nbalepur.github.io/Jordan:
https://users.umiacs.umd.edu/~jbg/Shi:
https://ihsgnef.github.io/Matt:
https://matthewshu.com/