科学教育本科专业网站建设的设计与实践     

胡兴昌  仲晓烨 《科学教育》2011,(5)

专业网站建设是高等学校教学质量与教学改革工程的重要组成部分,其目的是实现优质教学资源的充分交流与共享,全面提高教学质量。本文就科学教育专业主题网站建设的研究背景、网站建设的内容、各平台功能模块的设计等进行了分析和探讨,并在了解各种支持技术,对其进行广泛的比较研究基础上,针对目前科学教育专业网站建设研究现状与科学教育专业网站建设的需求进行分析,努力为本专业发展营造良好的环境和条件。  相似文献   

在线论坛中学习者兴趣与行为主题联合建模研究     

张思  陈娟  夏丹  王涛  王志锋  刘清堂 《远程教育杂志》2022,(1)

在线论坛中的文本大数据,能够在一定程度体现学习者的个人情感与知识建构水平,对其进行深入挖掘能为个性化教学提供参考与依据。针对教育文本挖掘现有研究对兴趣和行为进行孤立分析的现状,将学习者潜在的兴趣主题和行为倾向纳入主题模型,构建了融合行为-情感-主题-时间的潜在语义分析模型,即BETTM(Behavior-Emotion-Time-Topic Model),以致力于挖掘四者之间的潜在关系。基于华中地区某高校开设课程的在线论坛数据,通过挖掘学习者在整个教学周期中的兴趣主题与行为倾向,探究二者与学习成绩的关系,以及二者随时间变化的规律。结果表明:(1)有关资源查找和组内成员之间交互的主题,对学习成绩有显著正向作用;(2)教学作品完成过程中学习者的信息发布行为,对学习成绩有正向影响作用;(3)兴趣主题和行为倾向联合后的12类行为分布,对学习成绩没有显著影响;(4)在时间上,前期学习者倾向于对资料进行查找与整合以及分配任务,中期则关注彼此的交互和个人观点的表达,后期更侧重于对作品修改和完善,以及对自己和他人在整个讨论过程中表现进行评价。研究所提出的模型,为在线论坛中学习者兴趣与行为主题挖掘、分析与预测,提供了参考和依据。  相似文献   

Improving neural topic modeling via Sinkhorn divergence     

《Information processing & management》2022,59(3):102864

Textual data have been a major form to convey internet users’ content. How to effectively and efficiently discover latent topics among them has essential theoretical and practical value. Recently, neural topic models(NTMs), especially Variational Auto-encoder-based NTMs, proved to be a successful approach for mining meaningful and interpretable topics. However, they usually suffer from two major issues:(1)Posterior collapse: KL divergence will rapidly reach zeros resulting in low-quality representation in latent distribution; (2)Unconstrained topic generative models: Topic generative models are always unconstrained, which potentially leads to discovering redundant topics. To address these issues, we propose Autoencoding Sinkhorn Topic Model based on Sinkhorn Auto-encoder(SAE) and Sinkhorn divergence. SAE utilizes Sinkhorn divergence rather than problematic KL divergence to optimize the difference between posterior and prior, which is free of posterior collapse. Then, to reduce topic redundancy, Sinkhorn Topic Diversity Regularization(STDR) is presented. STDR leverages the proposed Salient Topic Layer and Sinkhorn divergence for measuring distance between salient topic features and serves as a penalty term in loss function facilitating discovering diversified topics in training. Several experiments have been conducted on 2 popular datasets to verify our contribution. Experiment results demonstrate the effectiveness of the proposed model.  相似文献   

TDTMF: A recommendation model based on user temporal interest drift and latent review topic evolution with regularization factor     

《Information processing & management》2022,59(5):103037

This paper constructs a novel enhanced latent semantic model based on users’ comments, and employs regularization factors to capture the temporal evolution characteristics of users’ potential topics for each commodity, so as to improve the accuracy of recommendation. The adaptive temporal weighting of multiple preference features is also improved to calculate the preferences of different users at different time periods using human forgetting features, item interest overlap, and similarity at the semantic level of the review text to improve the accuracy of sparse evaluation data. The paper conducts comparison experiments with six temporal matrix-based decomposition baseline methods in nine datasets, and the results show that the accuracy is 31.64% better than TimeSVD++, 21.08% better than BTMF, 15.51% better than TMRevCo, 13.99% better than BPTF, 9.24% better than TCMF, and 3.19% better than MUTPD ,which indicates that the model is more effective in capturing users’ temporal interest drift and better reflects the evolutionary relationship between users’ latent topics and item ratings.  相似文献   

教育学的坏理论研究之二：教育学的话题体系     

杨开城 《现代远程教育研究》2014,(1):3-10,19

任何理论都有其独立的命题网络。但教育学并不拥有自己的命题网络,倒是充满了各种争论性的话题。这些话题中,有些是其他学科＂观照＂教育的结果,本不属于教育学,也不是教育实践的核心关切,包括教育的起源、发展史、教育与其他事物的关系、教育者与受教育者的关系、所谓的教育规律和教育原理、各种教育的影响因素等等;有些话题无所谓结论,话题的争论本身似乎比结论更有吸引力,包括教育教学的本质、各种对象的构成要素和功能、教育是科学还是艺术、什么知识最有价值、教育是否具有相对独立性等等;有些话题只具有抽象的形而上学意义,比如教育的终极目的、各种教育主张以及相应的批判;有些话题只是职业行动规范及其解释,却被描述成了理论的样子。教育学拥有如此庞大的话题体系却让人体验到一种理论上的虚弱感。从性质上看,这些话题无法衍生出理论命题,这使得这个话题体系已经由曾经的学术成就转变为教育学难以摆脱的学术包袱。  相似文献   

Knowledge space oddity: How to increase the intensity and relevance of the technological progress of European regions     

Roberta Apa  Ivan De Noni  Luigi Orsi  Silvia Rita Sedita 《Research Policy》2018,47(9):1700-1712

This work contributes to previous research on the relationship between specific features of a regional knowledge space and the technological progress of the region. In particular, the main element of originality of this work is to have singled out the determinants of the technological progress intensity and relevance. We acknowledge the importance of knowledge assets for new knowledge production, and we identify path-dependent processes that allow a region to become increasingly competitive in terms of innovation potential. In particular, adopting an evolutionary view of regional development, we describe the regional knowledge space through four crucial characteristics: 1) technological knowledge base, 2) technological cumulativeness, 3) technological diversification, and 4) technological relatedness. We then measure to what extent each of the knowledge space’s characteristics differently affects the technological progress intensity and relevance of the region. A longitudinal study of 269 European regions over the period 1996–2012 was organized using data from REGPAT and Eurostat databases. Results show that technological relatedness affects positively both the intensity and relevance of the technological progress of European regions and that the other components of the knowledge space show a different impact on the two features of the technological progress. Finally, implications for EU policies supporting and stimulating regional technological progress are discussed.  相似文献   

Wikipedia bi-linear link (WBLM) model: A new approach for measuring semantic similarity and relatedness between linguistic concepts using Wikipedia link structure     

《Information processing & management》2023,60(2):103202

Wikipedia links its articles by manually defined semantic relations called the Wikipedia hyperlink (link) structure. The existing Wikipedia link-based semantic similarity (SS) and semantic relatedness (SR) computation models, such as Wikipedia one-way link (WOLM) model and Wikipedia two-way link (WTLM) model, do not assess the strengths of the relationships between a candidate concept and its links (out-links or in-links). These models treat all the links as equally important even though some links are semantically more influential than others and should be given more importance. This phenomenon reduces the accuracy of these models. This paper presents the Wikipedia bi-linear link (WBLM) model that extends the previously proposed WOLM and WTLM models. The WBLM model explores the Wikipedia link structure as a semantic graph and discovers the strongly (bi-linear links) and weakly (out-links or in-links) connected links of a candidate concept. It improves the link-based vector representations of concepts by assigning weights to their connected links according to the strengths of their semantic associations. The experimental results demonstrate that the proposed WBLM model significantly improves the SS and SR computation accuracy of the WOLM model (6.9%, 8%, 24%, 17.3%, 31.2%, 30.6%, 26.5%, and 35.4%) and WTLM model (1.2%, 3.9%, 7.1%, 9.9%, 11%, 6.3%, 12.7%, and 13%), in terms of linear correlations with human judgments on gold standard benchmarks, including MC30, RG65, WS203, SimLex, 353All, MTurk287, MTurk771, and MEN3000, respectively. Moreover, this research offers a deep insight into the Wikipedia link structure and provides an adequate base for understanding it as a semantic graph.  相似文献   

Multi-channel hypergraph topic neural network for clinical treatment pattern mining     

《Information processing & management》2023,60(4):103376

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