• <tr id="yyy80"></tr>
  • <sup id="yyy80"></sup>
  • <tfoot id="yyy80"><noscript id="yyy80"></noscript></tfoot>
  • 99热精品在线国产_美女午夜性视频免费_国产精品国产高清国产av_av欧美777_自拍偷自拍亚洲精品老妇_亚洲熟女精品中文字幕_www日本黄色视频网_国产精品野战在线观看 ?

    Abstracts

    2021-11-05 00:44
    中國遠程教育 2021年10期
    關(guān)鍵詞:英文

    Building new infrastructure for educational informatization: standards and implementation

    Zhiting Zhu, Qiuxuan Xu and Yonghe Wu

    In July 2021, the Chinese Ministry of Education and six other departments issued the document Guidance on Promoting the Construction of New Infrastructure for Education and Building a High-quality Education Support System. The concept of new infrastructure for education (hereinafter referred to as "new infrastructure"), as suggested in the document, centers on informatization, highlighting the basic and supportive role of informatization in education development. Therefore, this article aims to discuss standards required for the new infrastructure and potential approaches to its construction. The article starts with the national policy background, core mission, system framework and functional characteristics (intelligence, integration, green, governance, resilience, ubiquitous connectivity, and ecology) of the new infrastructure. It then, based on a demand analysis, develops a framework of standards for the new infrastructure which is composed of four aspects: digital base, system specifications, application scenarios, and goal-guidance. Finally, it puts forward ten suggestions on the construction of the new infrastructure. It is hoped that what is discussed in this article has implications for digital transformation of Chinas education.

    Keywords: educational informatization; new infrastructure; digital transformation; standard; action suggestions; digital base; ubiquitous networking; education data governance

    Using learning performance prediction model to predict the relationship between physical exercise and classroom behavior

    Hang Hu and Yaxin Li

    Learning behavior diagnosis, monitoring and evaluation has attracted significant research attention from the field of educational data mining. Research on learning performance prediction has shifted from data modeling to application in reality. Nevertheless, there is little research integrating multiple types of learning behavior data to predict and evaluate learning performance. This study collected the exercise logs and classroom learning videos of 1,053 students in a 12-week period. It developed predictive indicators of physical exercise and classroom behavior, adopted decision trees and rule algorithms to gene- rate intuitive and readable decision tree graphics and rule sets, and constructed early-warning threshold intervals and behavioral early-warning strategies. The machine deep neural network classification model was used together with the principal component and entropy method to obtain the weight and score interval of the two behaviors and develop the strategy of behavior combination evaluation. Findings show that the learning performance prediction model can effectively predict the impact of physical exercise and classroom behavior on learning performance, that early-warning strategy for learning behavior can effectively identify patterns of change in leaning behavior, and that the strategy of behavior combination evaluation can quantify the relationship between behavior characteristic values ??and learning performance, hence able to improve teaching management and education governance.

    Keywords: learning performance; prediction model; decision tree; deep learning; physical exercise beha- vior; classroom behavior; strategy research; relationship research

    Cultivating interdisciplinary creativity: theoretical mechanism and model reconstruction

    Baichang Zhong and Xiaofan Liu

    With increasing convergence of disciplines, interdisciplinary education such as robotics education, maker education and STEM plays an important role in cultivating student creativity. The construction of an effective teaching model is essential to the cultivation of student interdisciplinary creativity. It is argued that there are two major approaches. One is the use of the broad concept of interdisciplinarity to inform the cultivation practice. The other is the combination of reverse teaching with reverse engineering to further specify cultivation practice. Based on the arguments above, this article set off to re-interpret and re-construct the 4C teaching model previously developed to cultivate student interdisciplinary creativity.

    Keywords: creativity; 4C teaching model; interdisciplinary education; interdisciplinary creativity; reverse engineering; creative talent cultivation; STEM; deep learning

    Education in normal, new normal, and next normal

    Aras Bozkurt and Ramesh Chander Sharma

    The COVID-19 pandemic has consequences not only on a biological but also on a social and educational scale. The authors argue that the pandemic as a crisis is a milestone in the history of mankind and that the magnitude of its impact can be referred to as the Great Reset with many consequences which are still not known. We make fatal errors while pivoting to emergency remote education, for example, imitating face-to-face education, over-relying on digitally empowered practices and blindly believing in digital solutions. These educational sins compromise the effectiveness of our pedagogical responses, result in digital burnout and fatigue, and further widen digital divide. Consequences for a post-COVID world are also discussed. Online globalization is on the rise, meaning that education should reposition itself in the changing world. In the new normal, digital learning ecosystems promise a lot but also require us to approach issues such as privacy concerns, surveillance and ethics with caution. The silver lining of the pandemic is perhaps rising awareness of the value of openness in education. Likewise, the pande- mic requires us to rethink care and empathy as vital ingredients of learning which were forgotten long ago in many educational practices. Yet, the pandemic itself is a test for higher education, enabling us to see where we have failed and succeeded. Hybrid and blended modes of education are expected to be the next normal, but we need to find the right mix if we truly want to achieve an ideal learning ecosystem. Finally, this article suggests that educators should be alchemists, turning the crisis into an opportunity to reimagine, redesign and recalibrate the educational system for a better future.

    Keywords: Covid-19; education; new normal; emergency remote education; pandemic pedagogy; openness; digital burnout; digital fatigue; digital divide; digital ethics

    (英文目次、摘要譯者:肖俊洪)

    猜你喜歡
    英文
    英文摘要
    英文摘要
    英文摘要
    英文摘要
    英文摘要
    英文摘要
    英文摘要
    英文摘要
    剑河县| 五大连池市| 崇州市| 呼和浩特市| 长沙市| 新化县| 唐河县| 高碑店市| 黎城县| 江津市| 阳泉市| 永靖县| 晋城| 柳江县| 沙洋县| 抚宁县| 大关县| 皮山县| 益阳市| 于田县| 横山县| 千阳县| 同江市| 孟州市| 大足县| 永新县| 谷城县| 西贡区| 阿克陶县| 凉城县| 高平市| 平定县| 汉阴县| 晋宁县| 蕲春县| 东乡族自治县| 五峰| 南开区| 衡水市| 金坛市| 沁源县|