基于web2.0的教师教育网络课程设计与开发的案例研究

教师教育网络课程要注重教学内容、教学资源、教学策略、学习活动、学习评价、学习支持服务等要素的合理设计。在教学内容选取上要注重专业发展性和情境创设性;注重多种媒体教学资源的整合、优化,结构化资源和非结构化资源的配套使用;灵活采用多种学习策略和评价方式;充分利用WEB2.0社会性软件开展丰富多样的学习活动。以此来建设个性化、自主性、生成性、开放性、协作性与反思性的网络课程。     

高职英语教学中人文素质的培养

培养高职学生的人文素质意义重大。通过分析高职学生人文素质培养的重要性以及在公共英语教学中培养学生人文素质的可行性和必要性,提出了在公共英语教学中培养高职学生人文素质的原则及策略。     

在音乐教学中培养学生的自主探索能力

我国的教育模式正处于"应试教育"到"素质教育"的转型期,很多教师的教育方法还很落后,音乐教学也不例外.目前中小学音乐教学现状大致可归纳为两种:其一,从教学内容上主要为单一的教唱歌及为教唱而进行识谱教学.     

计算机组成原理课程导入教学的探讨

从课堂教学设计的各大因素讨论计算机组成原理第一节课"计算机系统概述"的具体设计,采用新颖有效的教学方法,探讨这些方法对知识传授、激发学生学习兴趣、发挥教师主导性和学生主体性产生的积极作用。     

小学生诗词楹联经典诵读开展方式的探究

诗词楹联是传统文化中的重要组成部分,读起来朗朗上口。诗词的历史非常悠久,从商周时期的《诗经》到唐诗宋词再到近代诗词,留给学生的是丰富的文化遗产。而楹联的历史也非常悠久,广义的楹联可以追溯到《诗经》时期,因为诗经中有很多对仗的语句,例如“昔我往矣,杨柳依依;今我来思,雨雪霏霏”等。狭义的楹联从五代后蜀主孟昶开始就已经非常普遍了。而到了明清时期,对对联的风俗非常盛行,对对联成为文人士大夫们重要的娱乐方式。可以说,诗词和楹联以其短小精悍的特点成为了古代流传最广的文学形式之一。因此,小学阶段朗诵诗词楹联是对传统文化的有力传承和发扬。     

新课程背景下提高高中数学课堂教学有效性的方法探究

随着教育改革的推进,对于高中数学教学的要求也在不断提高。高中数学内容复杂,学习难度大,知识点多,教学效果堪忧。为了有效提高高中数学的教学效率,教师要善于采用科学合理的教学方法。本文简要阐述了高中数学课堂教学的现状,从五个方面探讨如何最大限度地提高高中数学课堂教学的有效性。     

浅谈翻译教学在英语课堂中的应用

英语新课程标准提出要突出语言的实践性,强调语言技能的重要地位,翻译是一种综合运用语言技能的重要表现。当前我国英语教学对学生翻译技能的培养重视度较弱,本文分析了当前英语课堂中学生翻译水平的现状,并进一步提出将翻译教学应用于英语课堂中,提高学生的语用能力和语言技能。     

环境工程专业“环境化学”课程双语教学改革的实践与思考

双语教学是我国高校建设双一流大学的重要途径。本文结合环境工程专业的特点和人才培养需求,分析了环境化学课程双语教学的必要性和存在的问题,提出了启发-递进式教学模式、优选英文教材、优化教学内容、构建网络平台和建立多元化考核制等多种方法相结合的教学改革措施。     

Predicting future dynamics from short-term time series using an Anticipated Learning Machine

Predicting time series has significant practical applications over different disciplines. Here, we propose an Anticipated Learning Machine (ALM) to achieve precise future-state predictions based on short-term but high-dimensional data. From non-linear dynamical systems theory, we show that ALM can transform recent correlation/spatial information of high-dimensional variables into future dynamical/temporal information of any target variable, thereby overcoming the small-sample problem and achieving multistep-ahead predictions. Since the training samples generated from high-dimensional data also include information of the unknown future values of the target variable, it is called anticipated learning. Extensive experiments on real-world data demonstrate significantly superior performances of ALM over all of the existing 12 methods. In contrast to traditional statistics-based machine learning, ALM is based on non-linear dynamics, thus opening a new way for dynamics-based machine learning.     

Experiments on Cu-isotope fractionation between chlorine-bearing fluid and silicate magma: implications for fluid exsolution and porphyry Cu deposits

Hydrothermal fluid is essential for transporting metals in the crust and mantle. To explore the potential of Cu isotopes as a tracer of hydrothermal-fluid activity, Cu-isotope fractionation factors between Cl-bearing aqueous fluids and silicate magmas (andesite, dacite, rhyolite dacite, rhyolite and haplogranite) were experimentally calibrated. Fluids containing 1.75–14 wt.% Cl were mixed together with rock powders in Au₉₅Cu₅ alloy capsules, which were equilibrated in cold-seal pressure vessels for 5–13 days at 800–850°C and 2 kbar. The elemental and Cu-isotopic compositions of the recovered aqueous fluid and solid phases were analyzed by (LA-) ICP–MS and multi-collector inductively coupled plasma mass spectrometry, respectively. Our experimental results show that the fluid phases are consistently enriched in heavy Cu isotope (⁶⁵Cu) relative to the coexisting silicates. The Cu-isotope fractionation factor (Δ⁶⁵Cu_FLUID-MELT) ranges from 0.08 ± 0.01‰ to 0.69 ± 0.02‰. The experimental results show that the Cu-isotopic fractionation factors between aqueous fluids and silicates strongly depend on the Cu speciation in the fluids (e.g. CuCl(H₂O), CuCl₂^– and CuCl₃²⁻) and silicate melts (CuO_1/2), suggesting that the exsolved fluids may have higher δ⁶⁵Cu than the residual magmas. Our results suggest the elevated δ⁶⁵Cu values in Cu-enriched rocks could be produced by addition of aqueous fluids exsolved from magmas. Together with previous studies on Cu isotopes in the brine and vapor phases of porphyry deposits, our results are helpful for better understanding Cu-mineralization processes.