学分银行理念下开放教育综合实践教学改革初探     

谢妙忻  吴晓辉 《继续教育研究》2021,(1):33-36

随着信息技术日新月异、行业形态不断改变、新业态源源不断出现,社会对人才培养也随之提出更高的要求。在开放教育中,综合实践教学虽然处在战略性地位,但是在学习者专业技能培养中,往往只偏重于理论教育,实践技能教育存在流于形式、学习内容陈旧、实践资源缺失等问题,导致人才培养与实际岗位需求脱节。为了适应开放教育的发展趋势,结合当前开放教育综合实践教学中存在的实施不足、教学方式单一和实践基地弱化等问题,提出开放教育综合实践教学模式应以“学分银行”理念为基础,对综合实践教学进行行之有效的改革,以提升其教学质量和有效性。  相似文献   

“健康中国2030”战略下健康数据协同治理体系研究     

周知  胡昌平 《图书情报工作》2021,65(1):102-109

[目的/意义] 提升公民健康水平是经济社会发展到一定程度后的必然要求，健康数据协同治理体系的构建有助于从信息科学角度达成这一要求，治理体系需要以国家战略为宏观指导，全方位服务于公民健康水平提升的总体目标。[方法/过程] 通过对《"健康中国2030"规划纲要》文本精神的领会，在分析了各治理主体对健康信息治理需求的基础上，提出一种面向"健康中国2030"战略的健康数据协同治理体系，并针对关键环节提出保障措施。[结果/结论] 协调各层级、各部门与各利益主体的健康数据治理体系构建与保障，有助于在推动国家健康战略目标的同时实现健康数据的社会价值，拓展健康信息学的研究范畴。  相似文献   

新冠肺炎疫情报道中数据新闻的“工具化”衍变     

冯海青  朱昕磊 《传媒观察》2020,(5):12-16

在抗击新型冠状病毒疫情的众多新闻报道之中,数据新闻作品及数据可视化产品表现抢眼,效果独特,影响广泛,充分体现出数据新闻在新闻事件统计、分析、研判上的独特优势。大数据工具的介入,更让数据新闻从之前的"可视化"阶段衍变进入"工具化"阶段,成为此次公共卫生报道中值得研究的新形态。  相似文献   

数据驱动视野下高校智慧图书馆建设及服务规划——兼论“十四五”时期智慧图书馆发展路径     

邵波  许苗苗  王怡 《图书情报工作》2021,65(1):41-46

[目的/意义] 在科研全面数据化和“十四五”规划的背景下，高校图书馆建设方向和路径对教学和科研具有重大影响，本文旨在提出图书馆智慧化转型的下一步落地和实践思路。[方法/过程] 梳理高校图书馆发展现状，解析发展新态势，以数据意识为出发点，尝试构建智慧图书馆在技术、服务、空间等方面的发展方案。[结果/结论] 智慧图书馆的建设应重点在智能设备、智慧服务平台和智慧空间上“下深功”，此外还需在馆员角色和联盟建设上深入思考。  相似文献   

灰色预测法在情报研究中的应用研究综述     

张晶晶  李泽霞 《图书情报工作》2021,64(24):106-114

[目的/意义] 灰色预测法可有效处理情报研究中广泛存在的小样本数据，通过对灰色预测法在情报研究中的应用情况进行梳理，总结其在应用过程中存在的不足，为灰色预测法在情报研究中的进一步应用提供参考。[方法/过程] 通过综述情报研究中涉及灰色预测法的相关文献，从数据选取、模型构建和解决的问题等方面对情报研究中灰色预测法的应用进行概述，总结当前情报研究中灰色预测法的应用所存在的问题，并提出改进建议。[结果/结论] 在方法应用上，已有研究主要采用数列灰预测，且模型集中在单变量灰色预测模型，根据预测对象不同，灰色预测法已经在包括期刊分析、图书馆运行管理、热点主题分析及科研机构评价方面得到了很好的应用，未来可根据预测对象特点及研究目标尝试不同的灰色预测方法，扩宽灰色预测法在其他方面的情报研究问题中的应用。  相似文献   

Student success pocket-graphic: a mountain of data transformed     

Karen Briere  Kelly Drifmeyer 《Public Services Quarterly》2020,16(1):48-58

Abstract

How does a small community college library, without marketing experience or budget, advocate for its value to a campus community and its administrators? We did so by creating an engaging, bright, and easy-to-read “pocket-graphic.” In this column, we reflect on the process of shaping a multi-use product out of a mountain of data. Through research in design practices, field observations of popular information tools, and an uncomfortable step into braggadocio, we learned to articulate the successes of our library. Our “pocket-graphic” told our story, yes – but it also provoked surprise, questions (“you really have all that?”) and delight in the lesser known successes (“you really DO all that!”). In the process, we connected our students more deeply to helpful services and resources, faculty to supportive instruction, and positively changed the tone of conversation with all our stakeholders. By turning data points into selling points, we found insights and a focus that moved our own development forward, helping ourselves to define improved priorities for advancing our critical role in student success.  相似文献   

Caste-class association and school participation in Uttar Pradesh,India: Evidence from NSSO data     

《International Journal of Educational Development》2020

This study examines the impact of the caste-class association on enrolment in elementary education in Uttar Pradesh (UP), the largest state of India. Using data from the 71st round of NSSO, with the help of a probit model, it is found that class has a stronger impact on the enrolment ratio than caste in UP. There is a strong and direct association between caste and class at the extremes of the caste system. The association between upper-caste and upper-class significantly augments the enrolment ratio, while the association between lower caste and lower class adversely affects it. However, the cross-associations at the higher side of class, i.e., lower caste with the upper class significantly augments enrolment but the association between lower class with upper-caste is found to be adversely affecting the enrolment, though some of the interaction terms are insignificant statistically. This also ensures the dominance of class effect. This pattern is observed in the case of both rural and urban UP across genders.  相似文献   

RGAN-EL: A GAN and ensemble learning-based hybrid approach for imbalanced data classification     

《Information processing & management》2023,60(2):103235

Imbalanced sample distribution is usually the main reason for the performance degradation of machine learning algorithms. Based on this, this study proposes a hybrid framework (RGAN-EL) combining generative adversarial networks and ensemble learning method to improve the classification performance of imbalanced data. Firstly, we propose a training sample selection strategy based on roulette wheel selection method to make GAN pay more attention to the class overlapping area when fitting the sample distribution. Secondly, we design two kinds of generator training loss, and propose a noise sample filtering method to improve the quality of generated samples. Then, minority class samples are oversampled using the improved RGAN to obtain a balanced training sample set. Finally, combined with the ensemble learning strategy, the final training and prediction are carried out. We conducted experiments on 41 real imbalanced data sets using two evaluation indexes: F1-score and AUC. Specifically, we compare RGAN-EL with six typical ensemble learning; RGAN is compared with three typical GAN models. The experimental results show that RGAN-EL is significantly better than the other six ensemble learning methods, and RGAN is greatly improved compared with three classical GAN models.  相似文献   

Comfort assessment of running footwear: Does assessment type affect inter-session reliability?     

Julia Lindorfer  Josef Kröll  Hermann Schwameder 《European Journal of Sport Science》2019,19(2):177-185

Assessing comfort of running footwear reliably is challenging. The purpose of this study was to compare the intra-rater reliability between different assessment types, to calculate intra-individual reliability scores and to evaluate the effect of rater selection based on individual reliability scores on group level reliability. Three assessment types: ranking, Visual Analogue Scale (VAS), and Likert Scale (LS) were provided twice in six separate sessions among 30 participants, who assessed comfort of five shoes after treadmill running. Spearman's rho provided an evaluation of inter-session relative reliability and typical error as a measure of absolute reliability for each assessment type. Ranking (r?=?0.70, 95% confidence interval [CI] 0.61–0.78) yielded the highest relative reliability for overall comfort, followed by VAS (r?=?0.67, 95% CI 0.56–0.75) and LS (r?=?0.63, 95% CI 0.52–0.72), with large-scale overlaps of CIs between assessment types. The same order of assessment types was found for the percentage of reliable raters (r?≥?0.7) with 60% in ranking scale, 47% in VAS and 37% in LS. Forming subgroups corresponding to the intra-individual reliability substantially increased group level reliabilities. Based on measures of relative reliability, an extreme reduction in resolution as provided by the ranking from pairwise comparisons seems to be a valuable tool in footwear comfort assessments if assessment time is of minor importance. No preference can be provided for the two investigated rating scales. Besides the assessment type, a selection of the best raters in additional reliability checks seems to be a prerequisite for further comfort-related studies.  相似文献   

Self-training on refined clause patterns for relation extraction     

Duc-Thuan Vo  Ebrahim Bagheri 《Information processing & management》2018,54(4):686-706

Within the context of Information Extraction (IE), relation extraction is oriented towards identifying a variety of relation phrases and their arguments in arbitrary sentences. In this paper, we present a clause-based framework for information extraction in textual documents. Our framework focuses on two important challenges in information extraction: 1) Open Information Extraction and (OIE), and 2) Relation Extraction (RE). In the plethora of research that focus on the use of syntactic and dependency parsing for the purposes of detecting relations, there has been increasing evidence of incoherent and uninformative extractions. The extracted relations may even be erroneous at times and fail to provide a meaningful interpretation. In our work, we use the English clause structure and clause types in an effort to generate propositions that can be deemed as extractable relations. Moreover, we propose refinements to the grammatical structure of syntactic and dependency parsing that help reduce the number of incoherent and uninformative extractions from clauses. In our experiments both in the open information extraction and relation extraction domains, we carefully evaluate our system on various benchmark datasets and compare the performance of our work against existing state-of-the-art information extraction systems. Our work shows improved performance compared to the state-of-the-art techniques.  相似文献