物理化学“启发式教+探究式学”教育模式的构建与启示

基于化学史料中的物理化学家吉布斯的教育经验,构建一种新颖的“启发式教+探究式学”教育模式。“启发式教+探究式学”的模式对物理化学教学有重要的参考价值。从化学史中挖掘教育方法对探索化学教育方法有现实的借鉴意义。     

基于化学史的教学设计模型与应用

利用学科发展史进行教育由来已久, 但也受到多方面的质疑。针对提出的普遍性问题, 回顾或建立了5种化学史教学模型: 历史探究模型、科学故事模型、概念转变模型、科学论证模型和课程开发模型, 结合具体案例阐述了化学史教学的操作策略, 指出今后发展方向。     

一体化教学模式在涂料配方设计课程中的应用

介绍了高职背景下涂料配方设计课程的开展过程。采用一体化教学模式,从高职学生的特点入手剖析课程,使用课堂讨论、引发、对比等多种教学方法,使涂料配方设计课程的讲授取得了更好的教学效果。     

学习进阶本土化研究的意义及面临的问题

基于学习进阶(LPs)在美国新一轮科学教育改革中的重要地位和意义,结合我国科学教育新课程改革实施以来的进展与反思,阐述了学习进阶的本土化研究,对学生的认知发展、教师的教学与评价、课程标准及教科书的修订完善、科学素养的培养等方面的意义,分析了学习进阶的"本土化"研究过程中,在融入国内课程与教学、研究思路与方法等方面所面临的一些亟待解决的问题。     

《聚合物改性》课程线上教学的探索

本文分析了新冠疫情形势下《聚合物改性》课程线上教学实施的问题.依托"QQ课堂"和"超星学习通"平台,通过"在线讲授理论环节"和"居家实验"相结合的形式,开展了融"理论+实践"为一体的《聚合物改性》课程在线教学.把需要在实验室完成的实验生活化,既锻炼了学生的动手能力又能尝试自己制作的美食,既激发了学生的学习兴趣,又进行了...     

SPOC：结合高校教学的融合创新

从2008年开始,MOOCs经历了一个四年沉淀,两年爆发的发展历程.与以往的网络教育相比,名校名师效应、易学易用性的优势作用于教育资源绝对稀缺、网络环境大幅改善的环境,迅速点燃了人们强烈的学习动机,形成爆发式增长.在基于教学需求的探索过程当中,与传统教育方式的“融合创新”开始兴起,其中有一种非常值得关注的模式就是由Armando Fox教授提出的SPOC模式,哈佛、MIT、加州伯克利都在进行SPOC教学试验.在中国,清华大学出版社率先打造出SPOC平台,推出《大学物理》等课程,配套了完整的教学资源,开启了SPOC模式在中国的应用.     

物理美学对物理教学的意义

在实施新课程改革的大背景下,运用理论与实践相结合的方法就物理美学对物理教学的意义做了论述,以引起同行们对物理美学研究及其应用的关注．     

Discussion of the Application of Higher Education Psychology in University Physics Experiment Teaching——Attempted in Newton＇s Ring Experiment

随着现代教育的发展,关注大学生的学习心理研究,提高全体学生的学习效率和效果,教育心理学逐步走入课堂,越来越被教育工作者所重视。许多教师广泛采用教育心理学的原理和理论结构来指导自己的教学实践,并且取得了令人满意的成效。本文采用理论联系实际的方法,对高等教育心理学在牛顿环实验教学中的应用进行了有益探索。     

Extreme value laws in dynamical systems under physical observables

Extreme value theory for chaotic deterministic dynamical systems is a rapidly expanding area of research. Given a system and a real function (observable) defined on its phase space, extreme value theory studies the limit probabilistic laws obeyed by large values attained by the observable along orbits of the system. Based on this theory, the so-called block maximum method is often used in applications for statistical prediction of large value occurrences. In this method, one performs statistical inference for the parameters of the Generalised Extreme Value (GEV) distribution, using maxima over blocks of regularly sampled observable values along an orbit of the system. The observables studied so far in the theory are expressed as functions of the distance with respect to a point, which is assumed to be a density point of the system’s invariant measure. However, at least with respect to the ambient (usually Euclidean) metric, this is not the structure of the observables typically encountered in physical applications, such as windspeed or vorticity in atmospheric models. In this paper we consider extreme value limit laws for observables which are not expressed as functions of the distance (in the ambient metric) from a density point of the dynamical system. In such cases, the limit laws are no longer determined by the functional form of the observable and the dimension of the invariant measure: they also depend on the specific geometry of the underlying attractor and of the observable’s level sets. We present a collection of analytical and numerical results, starting with a toral hyperbolic automorphism as a simple template to illustrate the main ideas. We then formulate our main results for a uniformly hyperbolic system, the solenoid map. We also discuss non-uniformly hyperbolic examples of maps (Hénon and Lozi maps) and of flows (the Lorenz63 and Lorenz84 models). Our purpose is to outline the main ideas and to highlight several serious problems found in the numerical estimation of the limit laws.     

Statistics of Polymer Solutions from Scaling Concepts for Geometry and Relativistic Self-Diffusion in Liquids

Basic results on conformational statistics of polymer solutions are derived from recent scaling concepts for geometry and a relativistic picture for Brownian self-diffusion in liquid media. Any chain conformation is interpreted as a geometrical state affected by its end-to-end dimension, which here denotes the mean deviation between geodesic paths diffusing in the relativistic liquid phase. Statistical polymer length distributions solve an ondulatory equation in non-Euclidean manifolds for coil extension and shape. When length scale is vanishing, the size scaling is found again in terms of parallelism angle rotations. The characteristic chain ratio identifies instead an average metric coefficient, originating topologically from rotational degrees of freedom internal to single molecules.