KoroT-3E: A Personalized Musical Mnemonics Tool for Enhancing Memory Retention of Complex Computer Science Concepts
<|reference_start|>KoroT-3E: A Personalized Musical Mnemonics Tool for Enhancing Memory Retention of Complex Computer Science Concepts: As the demand for computer science (CS) skills grows, mastering foundational concepts is crucial yet challenging for novice learners. To address this challenge, we present KoroT-3E, an AI-based system that creates personalized musical mnemonics to enhance both memory retention and understanding of concepts in CS. KoroT-3E enables users to transform complex concepts into memorable lyrics and compose melodies that suit their musical preferences. We conducted semi-structured interviews (n=12) to investigate why novice learners find it challenging to memorize and understand CS concepts. The findings, combined with constructivist learning theory, established our initial design, which was then refined following consultations with CS education experts. An empirical experiment(n=36) showed that those using KoroT-3E (n=18) significantly outperformed the control group (n=18), with improved memory efficiency, increased motivation, and a positive learning experience. These findings demonstrate the effectiveness of integrating multimodal generative AI into CS education to create personalized and interactive learning experiences.<|reference_end|>
@article{yuan2024korot-3e:,
    title={KoroT-3E: A Personalized Musical Mnemonics Tool for Enhancing Memory
  Retention of Complex Computer Science Concepts},
    author={Xiangzhe Yuan, Jiajun Wang, Siying Hu, Andrew Cheung, Zhicong Lu},
    journal={arXiv preprint arXiv:2409.10446},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.10446},
    primaryClass={cs.HC}
}