Xiangzhe Yuan, Jiajun Wang, Siying Hu, Andrew Cheung, Zhicong Lu
{"title":"KoroT-3E:增强复杂计算机科学概念记忆的个性化音乐记忆工具","authors":"Xiangzhe Yuan, Jiajun Wang, Siying Hu, Andrew Cheung, Zhicong Lu","doi":"arxiv-2409.10446","DOIUrl":null,"url":null,"abstract":"As the demand for computer science (CS) skills grows, mastering foundational\nconcepts is crucial yet challenging for novice learners. To address this\nchallenge, we present KoroT-3E, an AI-based system that creates personalized\nmusical mnemonics to enhance both memory retention and understanding of\nconcepts in CS. KoroT-3E enables users to transform complex concepts into\nmemorable lyrics and compose melodies that suit their musical preferences. We\nconducted semi-structured interviews (n=12) to investigate why novice learners\nfind it challenging to memorize and understand CS concepts. The findings,\ncombined with constructivist learning theory, established our initial design,\nwhich was then refined following consultations with CS education experts. An\nempirical experiment(n=36) showed that those using KoroT-3E (n=18)\nsignificantly outperformed the control group (n=18), with improved memory\nefficiency, increased motivation, and a positive learning experience. These\nfindings demonstrate the effectiveness of integrating multimodal generative AI\ninto CS education to create personalized and interactive learning experiences.","PeriodicalId":501541,"journal":{"name":"arXiv - CS - Human-Computer Interaction","volume":"39 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"KoroT-3E: A Personalized Musical Mnemonics Tool for Enhancing Memory Retention of Complex Computer Science Concepts\",\"authors\":\"Xiangzhe Yuan, Jiajun Wang, Siying Hu, Andrew Cheung, Zhicong Lu\",\"doi\":\"arxiv-2409.10446\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As the demand for computer science (CS) skills grows, mastering foundational\\nconcepts is crucial yet challenging for novice learners. To address this\\nchallenge, we present KoroT-3E, an AI-based system that creates personalized\\nmusical mnemonics to enhance both memory retention and understanding of\\nconcepts in CS. KoroT-3E enables users to transform complex concepts into\\nmemorable lyrics and compose melodies that suit their musical preferences. We\\nconducted semi-structured interviews (n=12) to investigate why novice learners\\nfind it challenging to memorize and understand CS concepts. The findings,\\ncombined with constructivist learning theory, established our initial design,\\nwhich was then refined following consultations with CS education experts. An\\nempirical experiment(n=36) showed that those using KoroT-3E (n=18)\\nsignificantly outperformed the control group (n=18), with improved memory\\nefficiency, increased motivation, and a positive learning experience. These\\nfindings demonstrate the effectiveness of integrating multimodal generative AI\\ninto CS education to create personalized and interactive learning experiences.\",\"PeriodicalId\":501541,\"journal\":{\"name\":\"arXiv - CS - Human-Computer Interaction\",\"volume\":\"39 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Human-Computer Interaction\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.10446\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Human-Computer Interaction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.