论文标题
学生在COVID-19大流行期间学习科学的经验及其第二天的建议：希腊大学系案例研究
Students' experiences of learning Sciences during the Covid-19 pandemic and their suggestions for the next day: A Greek University Department case study
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
Around the globe Covid-19 pandemic has influenced not only the education, but also our everyday life, among other aspects. In Greece, distance learning started to get in use widely in tertiary education, since the first national lockdown was announced and reshaped education in many ways. In the University of Thessaly, in the Department of Mathematics, undergraduate students opt a lot of different courses to attend and due to the Covid-19 crisis all of them are taught via web platforms. Some of the most significant theoretical subjects are "Calculus" (with applications in Science and Mechanics), "Physics" (Classical Mechanics) and "Philosophy of Science". In addition, some other applied subjects are "Programming Languages" and "Digital Technologies in Mathematics Education" and the impact the above have, generally in education and society itself. In this paper, we describe the different ways students have reacted regarding learning Sciences in a distance learning environment. We split our case study in two parts. The first one is about the way students experience e-learning and the second one is about their suggestions for the next day. Integrating e-questionnaires and interviews and taking into account parameters like economic factors and the permanent residence issue, we asked the students about their preferences among face-to-face learning, distance learning and a blended model. Remarks about the academic life and the possible ways of taking the extra step, after the Covid-19 crisis ceases to exist, are made.
