While there is some research that explores the effects of using artificial intelligence in a classroom setting, there has been very little exploration into how machine-learning-reliant methods are compared to traditional study methods, specifically in the area of memorizing complex topics. This study analyzes the effects of replacing a student’s perceived learning efficacy of a subject with a natural language understanding (NLU) model. We compared the effects of studying with a spaced-repetition application that utilizes an NLU model to calculate a user’s understanding of material against the effects of studying with a spaced-repetition model that does not use NLU. We used our results to determine if replacing the self-assessment component of flashcard studying applications with an NLU model leads to better memorization and retention. We found that while both approaches produced similar results, the non-NLU approach produced slightly higher and more consistent memorization outcomes than the NLU approach.