{"title":"\"翻转 \"大学:法律硕士辅助终身学习环境","authors":"Kirill Krinkin, Tatiana Berlenko","doi":"arxiv-2409.10553","DOIUrl":null,"url":null,"abstract":"The rapid development of artificial intelligence technologies, particularly\nLarge Language Models (LLMs), has revolutionized the landscape of lifelong\nlearning. This paper introduces a conceptual framework for a self-constructed\nlifelong learning environment supported by LLMs. It highlights the inadequacies\nof traditional education systems in keeping pace with the rapid deactualization\nof knowledge and skills. The proposed framework emphasizes the transformation\nfrom institutionalized education to personalized, self-driven learning. It\nleverages the natural language capabilities of LLMs to provide dynamic and\nadaptive learning experiences, facilitating the creation of personal\nintellectual agents that assist in knowledge acquisition. The framework\nintegrates principles of lifelong learning, including the necessity of building\npersonal world models, the dual modes of learning (training and exploration),\nand the creation of reusable learning artifacts. Additionally, it underscores\nthe importance of curiosity-driven learning and reflective practices in\nmaintaining an effective learning trajectory. The paper envisions the evolution\nof educational institutions into \"flipped\" universities, focusing on supporting\nglobal knowledge consistency rather than merely structuring and transmitting\nknowledge.","PeriodicalId":501112,"journal":{"name":"arXiv - CS - Computers and Society","volume":"119 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"\\\"Flipped\\\" University: LLM-Assisted Lifelong Learning Environment\",\"authors\":\"Kirill Krinkin, Tatiana Berlenko\",\"doi\":\"arxiv-2409.10553\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid development of artificial intelligence technologies, particularly\\nLarge Language Models (LLMs), has revolutionized the landscape of lifelong\\nlearning. This paper introduces a conceptual framework for a self-constructed\\nlifelong learning environment supported by LLMs. It highlights the inadequacies\\nof traditional education systems in keeping pace with the rapid deactualization\\nof knowledge and skills. The proposed framework emphasizes the transformation\\nfrom institutionalized education to personalized, self-driven learning. It\\nleverages the natural language capabilities of LLMs to provide dynamic and\\nadaptive learning experiences, facilitating the creation of personal\\nintellectual agents that assist in knowledge acquisition. The framework\\nintegrates principles of lifelong learning, including the necessity of building\\npersonal world models, the dual modes of learning (training and exploration),\\nand the creation of reusable learning artifacts. Additionally, it underscores\\nthe importance of curiosity-driven learning and reflective practices in\\nmaintaining an effective learning trajectory. The paper envisions the evolution\\nof educational institutions into \\\"flipped\\\" universities, focusing on supporting\\nglobal knowledge consistency rather than merely structuring and transmitting\\nknowledge.\",\"PeriodicalId\":501112,\"journal\":{\"name\":\"arXiv - CS - Computers and Society\",\"volume\":\"119 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Computers and Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.10553\",\"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 - Computers and Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.10553","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The rapid development of artificial intelligence technologies, particularly
Large Language Models (LLMs), has revolutionized the landscape of lifelong
learning. This paper introduces a conceptual framework for a self-constructed
lifelong learning environment supported by LLMs. It highlights the inadequacies
of traditional education systems in keeping pace with the rapid deactualization
of knowledge and skills. The proposed framework emphasizes the transformation
from institutionalized education to personalized, self-driven learning. It
leverages the natural language capabilities of LLMs to provide dynamic and
adaptive learning experiences, facilitating the creation of personal
intellectual agents that assist in knowledge acquisition. The framework
integrates principles of lifelong learning, including the necessity of building
personal world models, the dual modes of learning (training and exploration),
and the creation of reusable learning artifacts. Additionally, it underscores
the importance of curiosity-driven learning and reflective practices in
maintaining an effective learning trajectory. The paper envisions the evolution
of educational institutions into "flipped" universities, focusing on supporting
global knowledge consistency rather than merely structuring and transmitting
knowledge.