日语教学中的母语语法问题

在学习和掌握母国语言的过程中,到底要不要学习语法?语法在外语教学与学习中起什么作用?母语的语法对外语学习有什么帮助?我们在《日语精读》课教学中发现,现在的许多大学生对汉语语法知识非常贫乏,对句子的语法成分不清楚。这种汉语语法知识的贫乏,直接导致学生对外语语法体系理解的困难,从而使外语教学的质量低、效率不高、效果不大。因此,笔者觉得有必要制定新的教育方针,加强母语语法的教学与研究,使得语法在教师的外语教学与学生的外语学习过程中发挥更大的作用。     

浅谈任务驱动在模拟电子技术教学中的应用

该文阐述了在模拟电子技术教学过程中采用任务驱动式教学的必要性和优越性,并就该课程在任务驱动模式下的教学设计和教学评价作了较详细的分析和介绍。     

浅议高职保险专业人才培养模式的改革

保险是与人打交道的行业,保险公司对一线员工综合素质要求较高,而我们现有的传统教学模式培养出的学生缺乏实践的锻炼、缺乏职业环境的熏陶,远未能符合保险公司用人的要求。为适应保险市场对一线人才的需求,高职高专保险专业必须进行改革,改变原有的人才培养模式和课程体系,进行工学交替、工学结合模式的改革和基于工作流程的课程体系改革。     

Antecedents and consequences of knowledge sharing in international tourist hotels

The purpose of this empirical study is to investigate factors which influence knowledge sharing, organizational learning and effectiveness. Of self-completed questionnaires collected from international tourist hotels in Taiwan, 615 were usable for data analysis. The structural equation modeling results showed that leaders played the roles of mentor, facilitator and innovator, and nurtured a supportive environment at the levels of workgroup, immediate superior and organization. In addition, employees had a positive attitude towards learning and to sharing. All of these contributions facilitate transformation of collective individual knowledge to organizational knowledge, resulting in the advancement of organizational learning, and thus, greater organizational effectiveness.     

汉字识别技术的研究进展分析

为全面深入地掌握汉字识别技术的研究现状与应用进展,基于WOS数据库中汉字识别研究领域的文献数据,利用 CiteSpace可视化软件进行文献计量与知识图谱分析。结果表明：中国的高校和研究所是汉字识别研究的核心力量;汉字识别技术的发展历程由早期的传统方法OCR技术演化为中期的联机手写汉字识别,再到近期基于深度学习的汉字识别研究;研究前沿为手写汉字识别、混合语言模型、生成对抗网络和场景文本识别;汉字识别技术将朝着高效率及智能化方向发展。     

The Effects of Four Dimensions of Strategic Orientation on Firm Innovativeness and Performance in Emerging Market Small- and Medium-Size Enterprises

We investigate the effects of technology, entrepreneurial, market, and learning orientations on firm innovativeness, and the mediating effect of firm innovativeness on these relationships, using a survey of 374 small- and medium-size enterprises in Korea. The results reveal that, while technology, entrepreneurial, and learning orientations significantly influence firm innovativeness, firm innovativeness has a significant effect on firm performance. We also find that firm innovativeness has a statistically significant mediating role in the relationships of technology, entrepreneurial, and learning orientations to firm performance. Our study contributes to strategic management and emerging market literature by identifying the pivotal role of innovativeness for firms that seek to benefit from various types of strategic orientations.     

Creating financial statements using FRx within Microsoft Dynamics GP: Learning vs. teaching

This project requires you to create financial statements using FRx within Microsoft Dynamics GP, an enterprise system. The project emphasizes the learner-centered paradigm rather than a teacher-centered educational paradigm. Researchers have found great importance in the learner-centered approach in educating students, especially in information systems (Landry, Saulnier, Wagner, & Longenecker, 2008; Saulnier, Landry, & Wagner, 2008). Major differences exist between the two approaches; for example, the professor gives information and evaluates, and emphasizes the right answer in a teacher-centered approach. The professor coaches and facilitates, and emphasizes that students generate good questions and learn from mistakes in a learner-centered approach. This project utilizes the learner-centered approach, an effective approach for you to use in today’s environment.     

Overcoming localization of knowledge — the role of professional service firms

The literature on organizational learning asserts that external learning is often limited geographically and technologically. We scrutinize to what extent organizations acquire external knowledge by accessing external knowledge repositories. We argue that professional service firms (PSFs) grant access to nonlocalized knowledge repositories and thereby not only facilitate external learning but also help to overcome localization. Focusing on patent law firms, we test our predictions using a unique dataset of 544,820 pairs of European patent applications. Analyzing patterns of knowledge flows captured in patent citations, we find that accessing a PSF's repository facilitates the acquisition of external knowledge. As the effect is more pronounced for knowledge that is distant to a focal organization, we conclude that having access to a knowledge repository compensates for localization disadvantages. Copyright © 2013 John Wiley & Sons, Ltd.     

Predicting Corporate Bankruptcy: An Evaluation of Alternative Statistical Frameworks

Corporate bankruptcy prediction has attracted significant research attention from business academics, regulators and financial economists over the past five decades. However, much of this literature has relied on quite simplistic classifiers such as logistic regression and linear discriminant analysis (LDA). Based on a large sample of US corporate bankruptcies, we examine the predictive performance of 16 classifiers, ranging from the most restrictive classifiers (such as logit, probit and linear discriminant analysis) to more advanced techniques such as neural networks, support vector machines (SVMs) and “new age” statistical learning models including generalised boosting, AdaBoost and random forests. Consistent with the findings of Jones et al. ( 2015 ), we show that quite simple classifiers such as logit and LDA perform reasonably well in bankruptcy prediction. However, we recommend the use of “new age” classifiers in corporate bankruptcy modelling because: (1) they predict significantly better than all other classifiers on both the cross‐sectional and longitudinal test samples; (2) the models may have considerable practical appeal because they are relatively easy to estimate and implement (for instance, they require minimal researcher intervention for data preparation, variable selection and model architecture specification); and (3) while the underlying model structures can be very complex, we demonstrate that “new age” classifiers have a reasonably good level of interpretability through such metrics as relative variable importances (RVIs).