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I do have an idea, and it revolves around adding best proven learning practices like : adding timers to help users revision a concept within some intervals like first its in a day , then its week etc , we can refer some resources and try adding these. |
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My vision for DeepTutor is for it to evolve from a query tool into a personalized cognitive mentor that recognizes learning as a fundamentally social act. It’s not just about providing the right answers through RAG, but about understanding a student's 'knowledge gaps' and guiding them through the process. To achieve true mastery, we must prevent learner isolation. I envision DeepTutor as a facilitator that not only interacts with the individual but also builds bridges between peers, suggesting collaborative spaces where students can contrast ideas and solve problems together. The goal is an ecosystem in which high-level AI tutoring and peer-to-peer support amplify each other, making digital learning a connected, deeply human experience. |
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感谢作者的辛勤付出,非常优秀的项目。从当前的DeepTutor功能来看将其定位为一个“研究助手”是否比“学习助手”更为恰当,项目其实已经具备“信息输入-信息整理-人机交互-应用拓展”几个模块,无论是研究人员、学生还是工程师都需要学习,但仅有学习是不够的,要能形成一个闭环管路,要以目标为导向才能学的更加高效、有用;事实上是不是这也更符合AI加持下的新型学习模式,学历、经验、年龄相对来说不再那么重要,学生与老师之间的界限不再明显,因为没有人比AI知道的更多,更重要的是使用者是否愿意花足够的时间精力去理解/思考/解决一个问题,这个过程中使用者如何利用好AI是关键能力之一,而DeepTutor将成为支撑这种能力的关键工具;对于信息输入,当前主要依赖使用者构建知识库,今后是否应该添加AI辅助的知识库扩展,比如根据知识库已有内容自动跟踪/推荐前沿进展(TrendRadar/Trendingpapers/已逝的paperswithcode都做挺好的);信息整理或许可以添加一些脑图自动生成功能,以便使用者更加直观/快速的抓住关键信息?;应用拓展,已经规划的代码生成是很重要的一个方面,但同时针对非技术用户进行参考格式/内容引导下的报告编写、图表生成、报表填写等或许能显著扩大用户群体。。。又或者通过插件库的方式对接不同的下游应用构建更加广泛的生态?想到哪写到哪,不当之处还请谅解 |
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