多媒体教学下学生学习风格多样性探讨

国内外教育专家研究发现,拥有多样性学习风格的学习者才是成功的学习者,也提出了在课堂教学中实现激发学生学习风格多样性的设想,但在课堂教学中激发学生学习风格多样性的深层次研究并不多见。文章主要介绍多媒体教学与学习风格多样性及增强学生学习风格多样性的意识。     

企业家学习研究方法现状评述与展望

企业家能力的成长和学习型组织的兴起使企业家学习成为企业管理领域的一个研究重点。通过搜索相关数据库对国内外企业家学习的相关文献与书籍的分析,本研究总结归纳了国内外研究企业家学习的研究方法。国外对于企业家学习的研究已经逐步趋向成熟,研究的方法多种多样而且非常规范,包括规范研究和实证研究;相对而言,国内的研究方法比较单一而且不够规范。国外对于企业家学习的研究定性分析居多．而国内则定量研究较定性研究多。因此,对于企业家学习的研究方法,除了多样性与规范性之外,定量研究和多学科交叉方法都为未来的研究提供了借鉴。     

食品专业英语多媒体网络课程设计

立足于本专业特点,利用计算机网络技术开发教学资源,建立食品专业英语网络课程。将教学内容与教学资源、同步测试、交流互动、知识拓展各功能模块有机结合,为学习者建构一个舒适的学习情境,加强了学生自主学习的能力。     

技术学习、业务转型与企业成长——东汽的案例研究

从集群学习到超集群学习的转化有助于企业成长转型的新探索。本文经过理论分析发现在集群网络演进的不同阶段,超集群学习的异地同产业学习、异地跨产业学习和本地跨产业学习等模式激发和促进了企业的技术学习和业务转型．提出了超集群学习模式与企业成长路径之间存在动态匹配关系的理论模型。在此基础上采用案例研究的方法,选取国内一家具有40年成长历史的大型重型装备企业作为研究对象,论证了企业超集群学习模式与企业成长路径之间的动态匹配关系。     

对学习要求与学习价值关系的探讨——从价值工程的视角

学习的价值工程理论认为,学习价值是学生获得的课程功能与学习成本的比值。对学习的不同要求,需要投入不同的成本,所以不同学习要求的学习价值是不同的,学习要求合理,学习具有较大价值;学习要求不合理,学习的价值较小或没有价值;如果学习要求严重偏离学生实际,会对学生身心造成极大的伤害,学习产生负价值。为了提高学生的学习价值,应当认真研究学生的智能结构,让学生学那些智能结构适宜、能够学好、爱好学的课程。     

复合媒介语境下英语学习媒体选择研究

此文基于调查,讨论了非英语专业学习者英语学习媒体应用与英语实际成绩的相关性。研究结果表明,与传统的英语学习媒体比较,基于多媒体的学习环境提供了更多的渠道可供学习者使用,相应地对学习者的学习成绩产生影响。对学习者所使用的各种教学媒体进行进一步研究具有实践意义,以期能够对学习者成绩的提高有所裨益。     

Collective learning in clusters: Mechanisms and biases

Although collective learning has long been considered a core feature of successful clusters, many researchers have treated the concept of learning more as a metaphor than a construct that requires an understanding of the various processes and mechanisms involved. I draw on the cultural-evolutionary perspective to argue that learning in clusters is an inherently biased process, with outcomes that can be both functional and dysfunctional. The cultural-evolutionary approach views learning as a process of imitation, treats beliefs as the unit of selection, and considers individuals as agents who are limited in their cognitive capabilities and social autonomy. Using interview data on 62 small business owners and 34 institutional actors in a textile and a surgical instruments cluster in South-west Germany, I show that the learning process can involve social biases which, in these cases, have the effect of reproducing a collective mindset built on distrust and rivalry. The findings provide an explanation for the fact that many studies of clusters have not been able to document the high levels of interfirm collaboration that cluster theory predicts.     

知识联盟中的学习障碍研究

知识联盟是企业获取外部知识的重要途径。然而 ,在知识联盟中却蕴含着各种形式的学习障碍 ,制约了知识的有效转移。本文首先从知识、企业和联盟对象三方面分析了联盟中学习障碍的状况及主要来源。     

A Direct Comparison of the Learning Outcomes from Training Programs and Job Experiences in Malaysian Organizations

ABSTRACT

In organizational settings, employees learn mainly through performing their jobs and by attending training programs. Empirical evidences that compare on the types and extent of learning occur from these two methods, however, are lacking and thus worthwhile examining. Hence, a questionnaire-based survey was conducted among one hundred seventy-five employees from various firms in Malaysia. This paper reports findings from the survey which addresses two main research questions: (1) What are the differences and similarities in learning outcomes of job experiences and formal training programs? and (2) Which method is superior? The respondents were asked to rate, using a five-point scale, five learning outcomes attributable to formal training programs and job experiences: recognition, job knowledge, communication and interpersonal skills, job quantity and quality, and independence and flexibility. The mean rating shows communication and interpersonal skills as the first-ranked learning outcome from both methods. On the other hand, recognition was ranked the lowest. T-test results indicate a significant overall superiority of job experiences over formal training programs. These and other findings imply important considerations in designing job and training in organizations. This paper calls upon organizations as well as individual employees to re-examine their approaches to workplace learning in order to obtain a synergetic learning impact from both job experiences and formal training.     

Multilevel IRT models for the analysis of satisfaction for distance learning during the Covid-19 pandemic

The Covid-19 pandemic played a relevant role in the diffusion of distance learning alternatives to “traditional” learning based on classroom activities, to allow university students to continue attending lessons during the most severe phases of the pandemic. In such a context, investigating the students' perspective on distance learning provides useful information to stakeholders to improve effective educational strategies, which could be useful also after the end of the emergency to favor the digital transformation in the higher educational setting.Here we focus on the satisfaction in distance learning for Italian university students. We rely on data comprising students enrolled in various Italian universities, which were inquired about several aspects related to learning distance.We explicitly take into account the hierarchical nature of data (i.e., students nested in universities) and the latent nature of the variable of interest (i.e., students' learning satisfaction) through a multilevel Item Response Theory model with students' and universities' covariates.As the main results of our study, we find out that distance learning satisfaction of students: (i) depends on the University where they study; (ii) is affected by some students' socio-demographic characteristics, among which psychological factors related to Covid-19; (iii) is affected by some observable university characteristics.     

Refined analysis and a hierarchical multi-task learning approach for loan fraud detection

Fraud problems in loan application assessment cause significant losses for finance companies worldwide, and much research has focused on machine learning methods to improve the efficacy of fraud detection in some financial domains. However, diverse information falsification in individual fraud remains one of the most challenging problems in loan applications. To this end, we conducted an empirical study to explore the relationships between various fraud types and analyzed the factors influencing information fabrication. Weak relationships exist among different falsification types, and some essential factors play the same roles in different fraud types. In contrast, others have various or opposing effects on these types of frauds. Based on this finding, we propose a novel hierarchical multi-task learning approach to refine fraud-detection systems. Specifically, we first developed a hierarchical fraud category method to break down this problem into several subtasks according to the information types falsified by customers, reducing fraud identification's difficulty. Second, a heterogeneous network with a meta-path-based random walk and heterogeneous skip-gram model can solve the representation learning problem owing to the sophisticated relationships among the applicants' information. Furthermore, the final subtasks can be predicted using a multi-task learning approach with two prediction layers. The first layer provides the probabilities of general fraud categories as auxiliary information for the second layer, which is for specific subtask prediction. Finally, we conducted extensive experiments based on a real-world dataset to demonstrate the effectiveness of the proposed approach.     

An Examination of Collaboration and Knowledge Transfer: China–Singapore Suzhou Industrial Park

abstract    This paper examines alliance knowledge transfer using a case study of the China–Singapore Suzhou Industrial Park (SIP), an alliance involving the Chinese and Singaporean governments, their agencies, and various private sector organizations. The objective is to extend existing knowledge in the alliance learning area and provide deeper understanding of some process-oriented aspects of alliance learning performance. We found that tacit knowledge was particularly difficult to transfer and that issues involving collaborative interactions between the partners both facilitated and impeded knowledge transfer. We also found that competitive learning occurred, which impacted the partner relationship and knowledge transfer.     

Channels of R&D spillovers: An empirical investigation of Swiss firms

Research and development (R&D) spillovers are, potentially, a major source of endogenous growth in various recent ‘new growth theory’ models. According to these models, firms engage in R&D in order to seek rents. Public aspects of this R&D then spill over to other firms, thereby creating increasing returns relating to scale and long-term growth. The actual mechanisms by which spillovers occur has, however, not been systematically studied. In order to provide empirical facts on this issue the paper investigates the effectiveness of various channels of R&D spillovers. The analysis is based on a survey conducted among 358 Swiss R&D executives representing 127 different lines of business, mainly in the manufacturing sector. The results can be summarized as follows. First, undertaking independent R&D was perceived by the R&D executives questioned as the most effective channel of R&D spillovers at the intra-industry level. This was followed by reverse engineering for product innovations and the utilization of publications and information from technical meetings for process innovations. Second, learning methods that rely on interpersonal communication were judged as moderately effective in the following order of importance: (i) publications and technical meetings; (ii) conversations with employees from innovating firms; and (iii) hiring away employees from innovating firms. The last method, especially, is not valued as effective in the Swiss context. Third, learning methods related to the patent system—licensing technology and patent disclosures in the patent office—were seen as moderately effective or not effective at all. Fourth, the effectiveness of the various channels of R&D spillovers varies from one industry to another. Fifth, the various channels of R&D spillovers can be reduced to subgroups, so that patterns of learning of competitive technology can be established.     

学业指导制度建设探析

学业指导工作的核心是从多角度、多层面挖掘各专业与社会需求的接洽点,从而制定相应的实施计划,提高教学质量。针对一、二年级的同学开展基础学业指导,重点进行学习规划,强化学习意识、提高学习主动性。对分院全体学生进行专业知识学习与应用指导,为后续深造和就业打下坚实的基础。让学生入学后就能了解所在专业的人才培养目标、培养计划,在校学习中知晓专业课程设置、专业方向、专业发展,毕业实习和就业实习期间掌握就业岗位、社会需求等信息。     

Teaching entrepreneurship using Massive Open Online Course (MOOC)

Entrepreneurship as a skill and process is increasingly being taught as a part of various university educational programmes. The literature is divided on the effectiveness of traditional methods to teach entrepreneurship. We consider the achievement of students learning outcomes in entrepreneurship course that is offered as a Massive Open Online Course (MOOC). The results suggest that the MOOC is a suitable platform to teach entrepreneurship as it provide tools to enable students? collaborative learning as well as improve individuals? affective key entrepreneurial aspects such as such opportunity recognition and resource acquisition.     

论语文探究性学习的策略

语文探究性学习,教师要努力营造良好的教学氛围和创设情境问题来激发学生的探究热情;教学中重视诵读,引导学生质疑,让学生在探究的过程中体验乐趣;广泛开展各种语文实践活动来培养学生的探究能力。     

IMAGES OF AN UNFOLDING DIVERSIFICATION PROJECT

This article studies a diversification-project in a medium-sized company from a cognitive perspective. Using a set of cognitive mapping techniques, it focuses on the images which the managers in this company have of the evolving diversification project in which they are involved. At the same time, it seeks to explore the organizational learning processes that arise during diversifying. It is suggested that a strict division of activities during the course of a diversification project may hamper organizational learning, as it excludes the possibility for acquiring shared experiences and thus of creating a common frame of reference. Consequently, it is argued that organizational learning during a diversification process may benefit from the active involvement (to some extent) of the various parties in each other’s activities.     

Entrepreneurial education and learning at universities: exploring multilevel contingencies

Abstract

Despite the worldwide increase in entrepreneurship education offered at universities, there is an ongoing debate whether and under which conditions this type of education contributes to students’ entrepreneurial learning. Building on human capital theory, we hypothesize that the exposure to various entrepreneurship education initiatives has an inverted U-shaped relationship with entrepreneurial learning outcomes. We also argue that this relationship is moderated by the entrepreneurial experience of the students, the teaching pedagogy applied in entrepreneurial initiatives offered at the university and the prevalence of opportunity-driven entrepreneurship in the country. A multi-level analysis on a cross-country sample of 87,918 students resulting from GUESSS (‘Global University Entrepreneurial Spirit Students’ Survey’) strongly confirms our hypotheses, and allows us to discuss implications for researchers, educators and policy makers with respect to the nature of entrepreneurial learning, the design of entrepreneurial education programs, as well as the contextual conditions that impact entrepreneurial learning outcomes.     

An Econometric Analysis of Polish Inflation Dynamics with Learning about Rational Expectations

Rational expectations modelling has been criticized for assuming that economic agents can learn quickly about and compute rational price expectations. In response, various authors have studied theoretical models in which economic agents use adaptive statistical rules to develop price expectations. A goal of this literature has been to compare resulting learning equilibria with rational expectations equilibria. The lack of empirical analysis in this literature suggests that adaptive learning makes otherwise linear dynamic models nonlinearly intractable for current econometric technology. In response to the lack of empirical work in this literature, this paper applies to post-1989 monthly data for Poland a new method for modelling learning about price expectations. The key idea of the method is to modify Cagan’s backward-looking adaptive-expectations hypothesis about the way expectations are actually updated to a forward-looking characterization which instead specifies the result of learning. It says that, whatever the details of how learning actually takes places, price expectations are expected to converge geometrically to rationality. The method is tractable because it involves linear dynamics. The paper contributes substantively by analyzing the recent Polish inflation, theoretically by characterizing learning, and econometrically by using learning as a restriction for identifying (i.e., estimating wth finite variance) unobserved price expectations with the Kalman filter. This revised version was published online in July 2006 with corrections to the Cover Date.