基于云计算的数字化教学资源设计能力质量评价方法研究

Zhang Fang-qin, Bai Yan
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引用次数: 0

摘要

为提高数字化教学资源设计能力的智能评价能力,优化质量评价模型,提出了一种基于云计算的数字化教学资源设计能力质量智能评价方法。采用数字化数据采集和统计分析方法进行数字化。教学资源设计能力质量统计样本序列抽样,采用云计算环境下数字化教学资源设计能力定量评价方法,构建数字化教学资源设计能力质量统计样本序列大数据分布模型,结合定量回归分析方法进行大数据特征提取和信息回归分析;构建数字化教学资源设计能力质量统计分析的特征提取模型,以教学资源分布状况为评价对象,结合定量递归分析方法对数字化教学资源设计能力质量统计样本序列进行自适应评价。采用总线设计与传感定量跟踪识别技术开展数字化教学资源设计能力质量体系建设,采用局部总线控制方法开展数字化教学资源设计能力质量智能预估负载指令,实现设计评价体系。测试结果表明,所设计的数字化学习资源能力评估智能质量评估系统具有良好的性能、良好的智能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Quality Evaluation Method of Digital Teaching Resources Design Capability Based on Cloud Computing
To improve the intelligent evaluation ability of digital teaching resource design ability and optimize the quality evaluation model, a cloud computing-based digital teaching resource design capability quality intelligent evaluation method was proposed. Digital data collection and statistical analysis methods were used for digitization. Teaching resource design capability quality statistical sample sequence sampling, using digital teaching resource design capability quantitative evaluation method in cloud computing environment, constructing big data distribution model of digital teaching resource design ability quality statistical sample sequence, combined with quantitative regression analysis method for big data characteristics Extraction and information regression analysis, constructing the feature extraction model of digital teaching resource design ability quality statistical analysis, taking the distribution status of teaching resources as the evaluation object, combined with quantitative recursive analysis method to carry out adaptive evaluation of digital teaching resource design ability quality statistical sample sequence. Adopting bus design and sensing quantitative tracking and recognition technology to carry out the system construction of digital teaching resource design capability quality, using local bus control method to carry out digital teaching resource design ability quality intelligence Estimated load instructions, to achieve design evaluation system. The test results show that the design of digital learning resources designed to assess the ability of intelligent quality assessment system has good performance, good intelligence.
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