互动式网络学习资源在英语写作教学中的应用

随着互联网的发展与普及,网络学习资源越来越多地出现在学生的日常生活中。本文采用问卷调查法探讨了大学生在英语写作方面采用网络学习资源前后的不同结果,在论述网络环境深层学习必要性的基础上提出一个以“互动”为中心,以提高大学生英语写作能力为主题的网络学习资源建设思路,并从学生与资源内容互动、学生与教师在线互动、学生与现实生活互动等几个方面,探讨了基于新课程标准的互动网络学习资源的设计理念与方法。     

数据挖掘技术支持下的大学生网络学习行为探讨

与课堂学习模式相比,网络学习缺乏监督与规范,学生的学习效果、学习效率很难得到有效保障。基于此,笔者先对网络学习行为和数据挖掘的概念进行分析,然后将数据挖掘技术应用于大学生网络学习行为分析领域,对大学生的学习行为与学习效果进行关联分析,在确定学生网络学习特点的基础上,进行大学生个性化网络学习平台设计,旨在帮助学生提升学习资源采集效率、提高学习行为质量。     

基于网络环境下的大学生学习能力培养

近几年来,随着互联网的迅速发展,丰富的网络资源和良好的网络环境给大学生的学习方法和学习方式带来巨大的改变,对提高大学生的学习能力起到非常重要的作用。如:通过网络视频进行自主学习,利用网络资源进行探究学习,以及利用网络工具进行协作学习。因此该文主要从自主学习、探究学习、协作学习等方面对基于网络环境下的大学生学习能力培养进行了探索,并在组建研究小组后,采用问卷调查、实地走访、网络交流等方式获取大量的数据,为该文的论点找到强有力的支持。     

基于WC-C-R学习资源推荐的研究

基于资源的学习已成为远程教育的一种重要的学习方式,网络课件和资源库是远程教育环境下两种重要的学习资源。为提高基于资源的学习效率,在“网络课件-概念图-学习资源库”三层模型研究的基础上,提出基于知识的资源推荐,并通过多Agent系统实现了在WC-C-R模型上进行资源推荐。实验证明,通过资源推荐,有助于提高学生的学习效率。     

大学生网络学习资源应用的现状分析

通过对洛阳师范学院不同专业、不同年级、不同性别的大学生网络学习资源应用情况进行调查,分析影响网络学习资源应用的具体因素,从有效应用的角度针对实际问题提出建议。     

个性化网络学习资源推荐系统研究

通过搜索资源来学习现已成为网络学习的一种重要的学习方式,为了提高这种方式下的学习效率,本文提出了一种基于Agent的网络推荐系统,通过获取学习者的当前学习需求,与内嵌的专家知识进行集成,利用多属性决策方法作为比较机制,以达到推荐合适学习资源的目的。系统还提出协同过滤方法,将相似学习者的学习资源推荐给学习者。最后。采用JADE平台开发了原型系统,并进行系统的集成和Web应用设计。     

基于学习分析的学生个性化学习资源推送

随着社会的发展,人们进行学习的方式也变的越来越多样化,随着移动学习、慕课等学习方式的出现,网络学习也进入人们的视野。由于互联网上的资源数量庞大、类型丰富,学习者检索困难,因此,对于个性化学习的资源推送的要求越来越高。本文构建了一个具有数据收集层、数据分析层和资源推送层的个性化学习资源精准推送模型,通过对学生的学习行为数据进行分析,进而找到最适合学习者特点的专属资源推送给学习者,来进行对学习效率的提高。     

西部大学生网络教育资源利用现状的调查研究

本文对西部在校大学生利用网络教育资源现状的抽样调查数据进行了详尽的分析,通过分析找出了大学生在利用网络教育资源时存在的问题,并提出了提高西部大学生利用网络教育资源进行学习的一些建议。     

基于网络和课堂的双平台自主学习的模式研究和构想

基于网络和课堂双平台的自主学习资源的开发及模式研究,充分利用网络技术与教学课堂有机结合,来提高课堂教学效率,培养学生的自主学习能力。网络技术进入了课堂,可以激发学生的学习兴趣,又有利于学生对课堂教学内容的理解和掌握。     

基于学习效率的学习资源推荐算法

针对目前网络学习系统学习资源推荐的不足,提出了一种基于学习效率的学习资源推荐算法。我们利用逻辑回归模型,以学习者学习前的测试结果作为输入,计算输出测验得分提高的最高期望值。该算法通过测验得分提高的期望值来量化学习效率,并通过推荐资源以最大化这个期望值。     

Productive use of learning resources in an online problem-based learning environment

This study examined students’ use of learning resources in a technologically-mediated online learning environment. Undergraduate student groups were engaged in an online problem-based learning (PBL) environment, rich with pre-selected video and knowledge resources. Quantitative and qualitative analyses showed that students accessed resources fairly frequently and benefited from them. Resources helped students construct a rich understanding of the problem and provided ideas for problem solutions. Detailed analyses of resource exploration along with contrasting case analyses between high-achieving and low-achieving student groups suggested that for learning to be effective in resource-rich environments, students first need to develop an understanding of the resources and learn how to access them efficiently. Second, students need to learn to process the contents of resources in meaningful ways so that they can integrate diverse resources to form a coherent understanding and apply them to solve problems. Finally, students need to develop knowledge and skills to use resources collaboratively, such as sharing and relating to each other’s resources. The results indicated that students, especially low-achieving students, need guidance to use resources effectively in resource-rich learning environments.     

Learning through inquiry: student difficulties with online course-based Material

Abstract This study investigates the case-based learning experience of 133 undergraduate veterinarian science students. Using qualitative methodologies from relational Student Learning Research, variation in the quality of the learning experience was identified, ranging from coherent, deep, quality experiences of the cases, to experiences that separated significant aspects, such as the online case histories, laboratory test results, and annotated images emphasizing symptoms, from the meaning of the experience. A key outcome of this study was that a significant percentage of the students surveyed adopted a poor approach to learning with online resources in a blended experience even when their overall learning experience was related to cohesive conceptions of veterinary science, and that the difference was even more marked for less successful students. The outcomes from the study suggest that many students are unsure of how to approach the use of online resources in ways that are likely to maximise benefits for learning in blended experiences, and that the benefits from case-based learning such as authenticity and active learning can be threatened if issues closely associated with qualitative variation arising from incoherence in the experience are not addressed.     

融入学习者模型在线学习资源协同过滤推荐方法

在线教育存在“信息迷航”问题,而传统的信息推荐方法往往忽视教育的主体—学习者的特征。本文依据教育教学理论,根据在线教育平台中的学习者相关数据,研究构建了适用于在线学习资源个性化推荐的学习者模型。以协同过滤推荐方法为切入点,融合学习者模型中的静态特征和动态特征对协同过滤方法进行改进,建立融入学习者模型的在线学习资源协同过滤推荐方法。以2020年3~7月时间段的东北石油大学“C程序设计”课程学生的真实学习数据和行为数据为数据集,对本文提出的方法进行验证和对比,最后证明本文提出的方法在性能上均优于对比方法。     

Supporting middle school students' online reading of scientific resources: moving beyond cursory,fragmented, and opportunistic reading

The abundant scientific resources on the Web provide great opportunities for students to expand their science learning, yet easy access to information does not ensure learning. Prior research has found that middle school students tend to read Web‐based scientific resources in a shallow, superficial manner. A software tool was designed to support middle school students in reading online scientific resources through three key strategies: making explicit a skim–read–summarize structure for online reading, using prompts to guide students' reading and foster articulation of thinking, and connecting reading to learning purposes. This study examined the differences between regular and guided online reading performed by eight pairs of sixth graders in a science inquiry project. The students' online reading processes and conversations were captured by a screen‐recording programme. Analysis of 60 h of screen videos showed that the students' online reading in the regular condition was cursory, fragmented, and opportunistic, while the structured online reading was more deliberate, thorough, and purposeful. Overall, the results suggest that middle school students' online reading of scientific resources needs to be guided.     

The role of perceived resources in online learning adoption

This study examines perceptions of adequate resources that can facilitate or inhibit students’ adoption of an online learning system, through an extension of the technology acceptance model (TAM) to include the perspectives of intra- and extra-organizational resources. The novel contribution of this study is the inclusion of internal and external-organizational factors in the aspect of perceived resources. The results of the study confirm the original TAM findings that perceived usefulness and perceived ease of use are positively associated with behavioral intention. In addition, the results also partially support that perceived resources have impacts on online learning adoption: Perceived ease of use, internal computing support, internal computing training, and external computing support have positive effects on perceived usefulness. Furthermore, internal computing support, internal computing training, external computing support, external computing training, and external equipment accessibility have positive effects on perceived ease of use. Recommendations for promoting adoption of the online learning system are subsequently discussed, along with suggestions for improving overall system design.     

网络环境下高职院校学生在线学习设计策略

信息化时代的发展,为网络教育的普遍应用提供了优越的条件。本文在对在线学习概念分析的基础上,针对目前高职院校学生在线学习现状及特点,结合在线学习活动构成要素,提出了高职院校学生在线学习活动的五项设计策略,以提高学生的在线学习能力。     

垂直学习社区基于学习兴趣与风格的社会化推荐算法

垂直学习社区包含了海量的学习资源,出现了信息过载现象,个性化推荐是解决这个难题的方法之一.但垂直学习社区中评分数据稀疏而文本、社交信息丰富,传统的协同过滤推荐算法不完全适用.基于用户产生的文本和行为信息,利用作者主题模型构建新的用户学习兴趣相似度衡量模型;根据用户交互行为信息综合考虑信任与不信任因素构建用户全面信任关系计算全面信任度;通过分析用户多维度学习行为模式,自动识别用户学习风格;最后提出融合兴趣相似度、全面信任度及学习风格的社会化推荐算法.用垂直学习社区网站CSDN实际数据集进行了实验分析.结果表明本文提出的推荐方法能更好向用户推荐其感兴趣的学习资源,有效地提高了推荐精度,进而提高用户学习效果.     

基于SSH架构和Android移动课程学习平台的开发

利用课程学习资源平台,已成为许多高校学生在课后进一步学习的一种重要途径。但由于传统课程学习平台需要利用传统互联网才能获取相关资源,这对资源学习带来了诸多不便。文中提出了一种基于Android的应用程序,结合Struts、Hibernate和Spring三层架构设计,利用操作简单、可视化和安全性较好的MySQL作为数据库管理系统,采用C/S和B/S双重开发模式,开发了移动化《计算机组成原理》课程学习资源平台。该学习平台可以利用手机和其他移动设备随时随地使用学习资源,实践证明该课程学习资源平台系统具有良好的稳定性和互动性。     

A blended learning lecture delivery model for large and diverse undergraduate cohorts

A blended learning model was developed to enhance lecture delivery in a large, diverse introductory psychology unit, introducing the use of an online, personalized learning system for lecture preparation and using lecture time to extend students' understanding. Changes to the assessment included diagnostic, formative and summative online quizzes. Using hierarchical multiple regression to account for the variance associated with prior achievement and background knowledge, the results show that students who completed the online formative assessments had significantly higher scores on summative assessment tasks, and that scores were even higher for students who used these resources repeatedly. Changes to future implementations of the model are suggested to improve student engagement in formative assessment, and to facilitate lecturer's use of reports on student progress to focus and improve the quality of discussion in the face-to-face lectures.     

结合学生行为模式分析的成绩早期预警研究

早期预警是在线学习中的重要主题,通过早期预警识别有不及格风险的学生可帮助教师及时开展个性化教学干预。使用深度学习模型对学生微观行为模式进行分析以提高早期预警的效果,并提出结合LSTM-autoencoder特征处理和注意力权重计算的不及格风险学生早期预警模型（LSTM-autoencoder and attention based early warning model,LAA）。该方法通过LSTM-autoencoder对学生行为时间序列数据进行特征处理,采用注意力机制计算关键预测因子。实验结果表明,LAA比基线模型取得更高的召回率,对低交互型和非持续型学生具有更好的识别效果,且能将教学干预时间提前;此外,该方法可识别影响成绩的关键周次和行为,可用于辅助教师开展在线教学指导。