科创中国

本研究调查了计算机辅助反馈策略对大学技术教育课程的影响.具体来说,研究探讨了计算机辅助反馈策略"对错反馈"(Knowledge of Responses,简称KCOR)和"正确答案反馈"(Knowledge of Correct Responses,简称KCR)的有效性,并与"无反馈"(No Feedback)的学生的学习态度进行了比较.三组学生被分配到三个条件之一:KOR,KCR和NR(对照组).通过四个星期的基于网络的教学实验,研究者获得学习者对计算机辅助反馈教学系略的态度.结果表明,学生对三种反馈显示出相同的态度.计算机辅助反馈策略可能是促进学习的可行的选择.

目前美国、韩国、中国台湾地区企业e-learning领域的发展走在世界前列.本文主要采用文献分析方法,通过搜索ProQuest数据库及CNKI中文数据库的关键研究文献,及通过梳理国际知名研究机构Bersin & Associates、ASTD、Brandon-hall等的研究报告,系统分析了这些国家和地区的企业e-learning 现状,并且对其发展趋势做了研究与预测.文章最后对我国企业e-learning发展提出了相应的政策建议.

Due to the large variations of environment with ever-changing background and vehicles with different shapes, colors and appearances, to implement a real-time on-board vehicle recognition system with high adaptability, efficiency and robustness in complicated environments, remains challenging. This paper introduces a simultaneous detection and tracking framework for robust on-board vehicle recognition based on monocular vision technology. The framework utilizes a novel layered machine learning and particle filter to build a multi-vehicle detection and tracking system. In the vehicle detection stage, a layered machine learning method is presented, which combines coarse-search and fine-search to obtain the target using the Ada Boost-based training algorithm. The pavement segmentation method based on characteristic similarity is proposed to estimate the most likely pavement area. Efficiency and accuracy are enhanced by restricting vehicle detection within the downsized area of pavement. In vehicle tracking stage, a multi-objective tracking algorithm based on target state management and particle filter is proposed. The proposed system is evaluated by roadway video captured in a variety of traffics, illumination, and weather conditions. The evaluating results show that, under conditions of proper illumination and clear vehicle appearance, the proposed system achieves 91.2% detection rate and 2.6% false detection rate. Experiments compared to typical algorithms show that, the presented algorithm reduces the false detection rate nearly by half at the cost of decreasing 2.7%–8.6% detection rate. This paper proposes a multi-vehicle detection and tracking system, which is promising for implementation in an on-board vehicle recognition system with high precision, strong robustness and low computational cost.

针对传统SVM主动学习中批量采样方法的不足,提出了动态可行域划分算法.从特征空间与参数空间的对偶关系入手,深入分析SVM主动学习的本质,将特征空间中对样本的标注视为参数空间中对可行域的划分;通过综合利用当前分类模型和先前标注样本两方面信息,动态地优化可行域划分方案,以确保选取的样本对模型改进的价值,最终实现更为高效的选择性采样.实验结果表明,基于动态可行域划分的SVM主动学习算法能够显著提高所选样本的信息量,从而能够在有限的标注代价下大幅提高其分类性能.

应用计划行为理论构建了大学生创业意愿影响因素模型.探讨了创业特质、创业认知、创业态度以及创业环境对创业意愿的影响关系.采用Amosl7.0对模型进行验证,结果表明:创业特质和创业认知影响创业态度的路径系数为0.555和0.668:创业态度和创业环境影响创业意愿的路径系数为0.626和0.443;创业特质和创业认知间接影响创业意愿的路径系数为0.347和0.418:创业态度是创业特质和创业认知影响创业意愿的中介变量.据此提出了三点对策建议.为培养大学生创业意愿和推进大学创业教育路径提供了可靠依据.

在分析社会标注对网络学习资源揭示的可行性基础上,从社会标注对网络学习资源的扩展揭示能力、不同教育资源网站中的标签揭示能力及教育领域标签与关键词揭示能力比较三个实证角度分析社会标注对网络学习资源的揭示能力,并提出社会标注揭示网络学习资源的多维模型.

入学数学准备是预测儿童小学学业成绩的有力指标,提高儿童的入学数学准备水平有助于提高儿童入学后的学业成绩、缩小儿童学习与发展的阶层差距和城乡差距.对浙江、江西、四川三省的1181名学前一年幼儿入学数学准备状况的城乡差异比较发现,城乡学前一年幼儿的数学学习与发展普遍存在不同步、不均衡的现象,关系领域的学习落后于数、量、形、空间等领域的学习;总体上,城市幼儿在多个领域的表现都优于乡镇和农村幼儿,城市幼儿与县城幼儿的表现没有显著差异.在普及学前教育发展的过程中,应加强对乡镇和农村幼儿的早期补偿教育,并加强关系领域的教学.