从辩证的视角下谈水中健身操项目

从辩证视角针对中国水中操发展现状、价值和作用等方面进行研究,为促进水中操的发展提供一定参考。研究结果表明,水中操是水中有氧运动项目,健身效果显著因而得到较快发展,但是目前发展中存在种种问题有待解决。     

南京市高校网球运动开展状况的调查分析

采用文献资料法和访谈法,对南京市20所高校网球运动的网球场地数量和种类、网球课程的设置、教学师资队伍建设、场地开放及收费情况等方面进行调查分析,以便能够发现并归纳影响网球运动在高校开展普及的不良因素,并根据存在的问题提出相应的对策和解决办法,为高校网球运动开展提供参考依据。     

应用测井资料识别准层序组界面的方法

在地层学理论研究、石油勘探开发中,层序地层分析有着重要的地位。其研究的关键是各级次层序界面的划分,以及内部的旋回结构解析。在研究过程中,由于岩心比较少、地震资料分辨率达不到精度要求等,为了更好的解决这些问题,在层序地层研究过程中需要应用较多的测井资料。测井资料具有很高的纵向分辨率,包含大量与沉积地层旋回变化有关的信息,是地层岩性和物性等的反映。通过不同方法科学的分析提取这些信息,会大大提高层序地层研究的定量化水平。不断提高测井资料的利用程度,充分发挥测井资料在层序地层学分析中的作用和应用范围,将有利的促进测井层序地层学的发展。     

玉米大斑病菌 STK1基因 DNA 片段的分离和纯化

玉米大斑病是玉米生产上的重要病害,分离和纯化玉米大斑病菌 STK1基因对于研究其致病性具有重要意义.根据 STK1基因 cDNA 序列设计特异性引物,以玉米大斑病菌基因组 DNA 为模板扩增得到 STK1基因 DNA 片段.该基因片段的分离和纯化,为进一步获得 STK1的完整基因,进行基因结构分析和该基因的突变体构建奠定了良好的基础.     

理论结合实践——谈怎样促进大学生践行科学发展观

科学发展观,第一要义是发展,核心是以人为本,基本要求是全面协调可持续,根本方法是统筹兼顾。大学生是社会发展的重要力量,他们是中国特色社会主义各项事业的生力军和接班人,承担着继往开来、迎接挑战、推动中国走向世界强国之林的历史使命。如何促进大学生在实践科学发展观中实现全面协调发展,对于建设社会主义和谐社会,加快推进社会主义现代化的宏伟目标,具有重大而深远的意义。     

信息与数字

2006年广播影视工作要点发布 1月23日,广电总局印发《2006年广播影视工作要点》,部署了2006年广播影视在舆论导向,宣传创新、安全播出、农村广电影视事业建设、数字化、影视制作产业、扩大对外覆盖和影响、体制机制改革、管     

谈幼师学生视唱能力的训练

视唱是幼师音乐课中的一门基础课程。视唱的目的在于训练学生的读谱能力 ,培养学生的音准、节奏感和乐感 ,为学习声乐、器乐打好基础。本文针对幼师学生的特点 ,结合自己的教学实践 ,对幼师学生视唱能力的训练 ,提出了有益的建议和方法     

A managerial perspective on institutions' administration readiness to diffuse blended learning in higher education: Concept and evidence

Abstract

There has been rapid development in Blended Learning (BL) diffusion and prior studies mainly focused on issues related to students and lecturers in improving teaching and learning outcomes, but very few studies focused on institution’s readiness and diffusion issues. Thus, there is need for institutional-based research to guide universities, colleges, and polytechnics to strategically diffuse BL. Accordingly, this study develops a model to investigate the variables and associated factors that influence institutions' administration readiness to diffuse BL initiatives based on Diffusion of Innovation (DoI) theory and institutional BL adoption framework that comprises of mature implementation stage of BL. Quantitative research approach was employed and data was collected using online survey questionnaire from 223 e-learning administrators/managers in Malaysia universities, colleges, and polytechnics. Next, Partial Least Square-Structural Equation Modeling (PLS-SEM) technique was employed for data analysis. Results indicate that institutional structure, resource support, technology infrastructure, management strategies, and ethical considerations are key variables that positively predict administration readiness to diffuse BL initiatives in higher education. Additional results from Importance Performance Map Analysis (IPMA) in PLS-SEM suggest that institutional structure has the strongest effect on administrators’ readiness to diffuse BL and is also the most important variable that influences BL diffusion in institutions. Theoretically, findings from this study provide insights on how institutions’ administration perception and acceptance of BL approach can be enhanced. Practically, the developed model can be employed as a readiness tool to assess institutions current state in implementing BL environment and further provides a road map for future improvement.     

Learner Groups in Massive Open Online Courses

The open nature of Massive Open Online Courses (MOOCs) attracts a large number of learners with different backgrounds, skills, motivations, and goals. This has brought a need to understand such heterogeneity in populations of MOOC learners. Categorizing these learners based upon their interaction with the course can help address this need and suggest possible improvements in course design and delivery. In this article, the K-means clustering technique with careful seeding is used to obtain clusters of learners having similar interaction in the course. Learners are grouped based on their interaction with course material, video lectures, discussion forums, and assessments. In the analysis of thirteen courses, the proposed method identified learners’ classes as Uninterested, Casuals, Performers, Explorers and Achievers. Each class of learners had distinct interaction with the course and followed a certain learning approach. The learners’ classes were mapped to the standard surface, deep, and strategic learning approaches.This article also highlights the data preparation phase and its importance in data mining.     

An ensemble approach in converging contents of LMS and KMS

Currently the challenges in e-Learning are converging the learning content from various sources and managing them within e-learning practices. Data mining learning algorithms can be used and the contents can be converged based on the Metadata of the objects. Ensemble methods use multiple learning algorithms and it can be used to converge the Learning Objects from Learning Management Systems (LMS) and Knowledge Objects from Knowledge Management System (KMS). This can increase the performance of the learning system, especially when there is different content available from a variety of models. In this research, Data mining ensemble techniques are used so that an appropriate learning content is delivered to the learner. By converging, the learning content from various sources the Learning system pedagogies can also be revolutionized and a right learning path can be provided to the learners. This research work uses various classification techniques for converging and are evaluated using statistical measures.