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本科生参与科研是我国研究型大学本科生教育改革的一项重要措施。为了提高本科生参与科研的能力,提出教研融合、以研促教的方法,并以离散数学课程为例,给出培养本科生科研意识、科研方法和科研精神的教学案例。 相似文献
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缪茸 《电子制作.电脑维护与应用》2014,(12)
应用型本科院校本科生毕业论文(设计)是高等院校各专业教学计划的重要组成部分,是学生毕业前的重要实践性活动和研究。但随着应用型本科院校的形成和不断发展,本科生毕业论文质量不能达到培养目标的要求。本项目提出基于工作过程导向的应用型本科毕业论文(设计)指导方法。强调以行动为导向,以教师和学生以及学生和学生之间互动的教学形式为方式,运用所学相关专业知识,完成毕业论文。 相似文献
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提出了一种评估软件项目人员流动风险的定量模型。该模型将关键人员占整体项目组成员人数的比例作为该模型的一项;流入、流出和更换关键人员数量分别占总关键人员数量的比例作为其他三项,并赋以后三项不同系数以区分其对项目的不同影响;同时考虑不同过程模型和处于模型中不同阶段使人员流动引起项目的风险程度也都不相同,又给以上三项赋以模型系数和阶段系数。模型中各系数通过公司的历史记录和专家评估获得。对该模型进行效果验证表明该模型科学合理、可以作为企业控制项目人员流动风险的依据。 相似文献
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游琪 《计算机与数字工程》2021,49(9):1878-1883
为了更准确地预测大学生转专业趋势,滨海大学2016~2019年连续四年专业本科生转专业的数据为基础,通过数学方法将灰色预测模型和马尔科夫预测模型两种数学模型结合起来,建立灰色马尔科夫模型,预测该大学未来几年学生转专业情况,从而推测大学生转专业的趋势.对得出的数据分析大学生转专业现象的原因,并对此提出相关建议. 相似文献
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There are disadvantages such as lack of resources and experience in college students’ entrepreneurship and the current research belong to the investigation
and research, lacking the prediction simulation model research. Based on the theory of individual learning and the theory of complex systems, this
study analyzes the mechanism of college students’ entrepreneurial process through dynamic learning theory, establishes the model of college students’
entrepreneurial subject, studies the different learning styles of college students, and discusses the influence of environmental dynamics on college students’
chance recognition. Through simulation and practice analysis, it is concluded that college students’ entrepreneurship is the process of learning and
development of an individual and enterprise subject. Simultaneously, this study finds that the improvement of learning efficiency, learning channels and
vision can effectively promote the development of enterprises, and can provide new ideas for the theoretical research of college students’ entrepreneurship. 相似文献
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为了对高校科研项目前景进行有效预测,进一步提升科研成果转化率,本文提出了基于神经网络结合科研项目共享的网络平台,构建可靠的科研项目前景预测系统。通过将各类大量科研项目的特征参数化,利用BP(反向传播)神经网络的非线性映射能力、自适应能力和对离散数据的泛化能力生成模型后,用于从多维度对一个新项目生成可靠的前景预测。实验表明,BP神经网络算法在大量学习经过预处理的样本后所产生的预测结果是具有较高准确性的,且能够随着新的样本输入不断更新和适应,因此该方法具有较强的可行性。 相似文献
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学业情绪能够影响和调节学习者的注意、记忆、思维等认知活动,情绪自动识别是智慧学习环境中情感交互和教学决策的基础。目前情绪识别研究主要集中在离散情绪的识别,其在时间轴上是非连续的,无法精准刻画学生学业情绪演变过程,为解决这个问题,基于众包方法建立真实在线学习情境中的中学生学习维度情感数据集,设计基于连续维度情感预测的深度学习分析模型。实验中根据学生学习风格确定触发学生学业情绪的学习材料,并招募32位实验人员进行自主在线学习,实时采集被试面部图像,获取157个学生学业情绪视频;对每个视频进行情感Arousal和Valence二维化,建立包含2 178张学生面部表情的维度数据库;建立基于ConvLSTM网络的维度情感模型,并在面向中学生的维度情感数据库上进行实验,得到一致性相关系数(Concordance Correlation Coefficient,CCC)均值为0.581,同时在Aff-Wild公开数据集上进行实验,得到的一致相关系数均值为0.222。实验表明,提出的基于维度情感模型在Aff-Wild公开数据集维度情绪识别中CCC相关度系数指标提升了7.6%~43.0%。 相似文献
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毕业设计是本科生最重要的实践环节。为提升计算机专业本科生毕业设计环节的教学质量,需要从选题、组织、答辩等多个环节采取措施。尝试类似科研项目立项、项目验收的形式进行毕业论文各环节的管理,能有效地提高毕业设计质量。 相似文献
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系统观是教育技术学研究中的一种基本观念和基本方法。基于系统观培养学生的计算机系统能力是现代计算机专业教学的重要目标。就系统能力培养以及实践教学的重要性、国内外计算机实践教学的现状进行介绍和分析,并在此基础上,提出基于系统观的计算机实践教学改革的一点思路。 相似文献
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In today’s modern society, the physical fitness of college students is gradually declining. In this paper, a prediction model for college students’ physical
fitness is established, in which support vector regression (SVR) and k-means clustering are combined together for the prediction of college students’ fitness.
Firstly, the physical measurement data of college students are classified according to gender and class characteristics. Then, the k-means clustering method
is used to classify the physical measurement data of college students. Next, the physical characteristics of college students are extracted by SVR to establish
the prediction model of physical indicators, and the model for predicting college students’ fitness can be obtained after scoring their physical fitness levels.
Finally, based on college physical test data of students at a university in China, the prediction results show that the method has high predictive accuracy
compared to other methods. 相似文献
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Jayalath Ekanayake Jonas Tappolet Harald C. Gall Abraham Bernstein 《Empirical Software Engineering》2012,17(4-5):348-389
It is crucial for a software manager to know whether or not one can rely on a bug prediction model. A wrong prediction of the number or the location of future bugs can lead to problems in the achievement of a project’s goals. In this paper we first verify the existence of variability in a bug prediction model’s accuracy over time both visually and statistically. Furthermore, we explore the reasons for such a high variability over time, which includes periods of stability and variability of prediction quality, and formulate a decision procedure for evaluating prediction models before applying them. To exemplify our findings we use data from four open source projects and empirically identify various project features that influence the defect prediction quality. Specifically, we observed that a change in the number of authors editing a file and the number of defects fixed by them influence the prediction quality. Finally, we introduce an approach to estimate the accuracy of prediction models that helps a project manager decide when to rely on a prediction model. Our findings suggest that one should be aware of the periods of stability and variability of prediction quality and should use approaches such as ours to assess their models’ accuracy in advance. 相似文献
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为了顺应教育"大数据"时代,设计了学员课程学习大数据体系架构,给出了基于该架构的学员课程学习成败预测模型,并进行了基于大数据的课程学习成败因素分析。通过挖掘学员大数据的价值,为学员课程学习给以提醒和建议,为教员提供了学员全面的学习情况和全过程反馈,从而不断提高教学效果。 相似文献