基于认知网络服务的移动学习在高等英语教育系统中的应用

Jing-Wen Chen
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引用次数: 0

摘要

学生在使用移动学习时可以选择各种学习途径和资源,这创造了一个通用的学习环境。为处理人工智能相关挑战而开发的机器学习技术被称为认知网络服务。适应的教育方法和良好的知识路径设计有助于实现随时学习的目标。此外,移动学习设备的显示能力正在成为学生的注意力和熟练时间的关键决定因素。获取必要的移动学习组件现在是一个热门问题。目前的移动学习环境不包括自适应的认知学习服务,以即兴制定预期服务的标准。实验结果表明,该方法的学生绩效率为92.11%,学生效率率为89.9,专业教学率为95.23%,错误率为43.86%,英语学习率为93.32%,互动性为92.5%,学习灵活性为94.86%,证明了系统的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Mobile Learning in Higher English Education Systems Using Cognitive Web Services
Students choose from various learning pathways and resources while using mobile learning, which creates a universal learning environment. Machine learning techniques developed to handle AI-related challenges are known as cognitive web services. Adaptive education methods and good knowledge path design can help achieve the goal of studying whenever. In addition, mobile learning devices' display capabilities are becoming a critical determinant of students' attention and time to proficiency. Getting the necessary mobile learning components is now a hot issue. Current mobile learning environments do not include cognitive learning services to be self-adaptive to improvise the standard of the intended service. Student Performance ratio 92.11%, Students' efficiency ratio 89.9, Professional teaching ratio 95.23%, Error rate 43.86%, English learning ratio 93.32%, Interactive ratio 92.5% and Learning flexibility ratio 94.86% are obtained as the experimental results for the suggested method, which proves that the system is more efficient.
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