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    • 停课不停学背景下对机能学实验虚拟实验平台建设的思考

    LIU Tianhua,CHENG Wei,ZHU Qingwen,GAO Wei,LI Haiyan,CHEN Yucai,NI Lei,ZHANG Sheng,ZHAO Shuying,ZHANG Li,GUO Jian

    Chinese Medicine Modern Distance Education of China（2022）

    Cited 1|Views44
    Abstract
    北京中医药大学积极响应教育部"停课不停学"的要求,借助机能学实验虚拟实验平台切实保障机能学实验教学工作的顺利开展.此文通过对"停课不停学"背景下的机能学实验课程以及机能学实验虚拟实验平台进行系统思考,并且结合问卷调查、教师走访、纵向比较等方法,分析"停课不停学"背景下机能学实验虚拟实验平台的使用效果和不足之处,旨在为虚拟实验"金"平台的建设提供参考和思路.
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    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
    • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
    • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
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    【要点】：本文探讨了在"停课不停学"政策背景下，北京中医药大学如何构建并评估机能学实验的虚拟实验平台，以保障教学继续进行，并提出了改进意见。
    

    【方法】：研究采用了问卷调查、教师访谈和纵向比较等方法来评估虚拟实验平台的使用效果。
    

    【实验】：通过对虚拟实验平台的使用情况进行分析，该平台允许学生在疫情期间继续进行机能学实验学习，结果揭示了其教学效果与存在的问题。