أثر استراتيجية إتقان التعلم في تحصيل طلاب مقررات تقنيات التعليم في كلية المعلمين بجامعة أم القرى و اتجاهاتهم نحوها

The objective of this study is to know the cffect of applying the strategy of education in the subject of technological learning for students in the Teachers’ College at Umm Al-Qura University. The study was applied to a group of students to know the effect, and attitudes towards the subjects they have studied. The findings of study have shown significant differences between the groups of study for the expense of both groups which studied the educational subject in the way of their studies to the accuracy of both levels of study’s achievements and students attitudes towards the subject. This means that this strategy increased the outcomes of students, and also, increased their attitudes towards the subject. Accordingly, the above two researchers recommend the use of strategic learning for accuracy in the teaching of the difference of educational technology subjects, and other subjects for their advantage to the students’ abilities in acquiring different skills. Also, they recommend that ministry of higher education, and ministry of education should put general plans to show teachers the curriculum and to let them practice wavs to achieve easily the objectives of learning for accuracy

Dynamic and Interactive Tools to Support Teaching and Learning

The use of technological learning tools has been increasingly recognized as a useful tool to promote students’ motivation to deal with, and understand, mathematics concepts. Current digital technology allows students to work interactively with a large number and variety of graphics, complementing the theoretical results and often used paper and pencil calculations. The computer algebra system Mathematica is a very powerful software that allows the implementation of many interactive visual applications. The main goal of this work is to show how some new dynamic and interactive tools, created with Mathematica and available in the Computable Document Format (CDF), can be used as active learning tools to promote better student activity and engagement in the learning process. The CDF format allows anyone with a computer to use them, at no cost, even without an active Wolfram Mathematica license. Besides that, the presented tools are very intuitive to use which makes it suitable for less experienced users. Some tools applicable to several mathematics concepts taught in higher education will be presented. This kind of tools can be used either in a remote or classroom learning environment. The corresponding CDF files are made available as supplement of the online edition of this article.

Technological Capabilities of Medium-Sized Contractors in Indonesia

The construction industry plays a significant role in national development and economic growth of Indonesia. Contractors are key actors in the construction industry and manage large amounts of construction resources and activities. While the demand for improving the nation's infrastructure is on the rise, the question remains whether the industry, especially contractors, will be able to fulfil this demand. This study investigates whether contractors include technological capabilities as an important part of their company strategies for addressing the dynamics of the construction industry. In particular, it aims to understand how contractors develop and improve their technological capabilities through a technological learning process (exploration, acquisition and internalisation). The investigation focuses on medium-sized contractors, who often play an important role as part of the supply chain for larger contractors. A model is developed to represent the dynamic interactions between key factors that influence the way contractors select and use technology to enhance their performance. Data were collected through a survey and were then used to map the contractors' development of technological capabilities. The study reveals that medium-sized contractors have yet to consider the development of technological capabilities as strategic. The results are expected to benefit the regulator and construction companies in Indonesia in their efforts to improve the performance of the country's construction industry.

Cybersecurity Leaders: Knowledge Driving Human Capital Development

Cybersecurity leaders must be able to use critical reading and thinking skills, exercise judgment when policies are not distinct and precise, and have the knowledge, skills, and abilities to tailor technical and planning data to diverse customers’ levels of understanding. Ninety-three percent of cybersecurity leaders do not report directly to the chief operating officer. While status differences influence interactions amid groups, attackers are smarter. With the aim of protecting organizations and reducing risk, knowledge about security must increase. Understanding voids are costly and increased breach chances are imminent. Burning questions exist. What are needed technological learnings for cybersecurity leaders to become smarter and remain ahead of attackers? How might these technologies hasten the understanding of the ‘what,’ ‘how,’ and ‘why’ reasons and key drivers for organizational behaviors. This article offers comparative analyses for cybersecurity leaders to engage in the questioning of practices, scrutinize entrenched assumptions about technology, customary practices, and query technology’s outputs by pursuing to comprehend all assumptions that could influence operations. Because understanding continues to rely upon progressively multifaceted epistemic technologies, outcomes of the research suggest that the salience of status distinctions is of central significance to the development of ongoing and proactive technological learning and up scaling solutions.

A Study of Technological Innovation in New Zealand

<p>This thesis addresses the research problem of "what are the key underpinning assets or drivers of technological innovation, and how can they be harnessed to create competitive advantage?" Technological change is an evolutionary process. Research and technological innovation creates knowledge and technology that is irreversible in the sense that inventions can be superseded but not "uninvented". Technological innovation creates knowledge and technology that is cumulative because it lays a platform for further knowledge creation, or sets in place another rung in an ascending ladder of new performance characteristics or properties which are demonstrably superior to their antecedents. In turn, the asset specificity and irreversibility of technology and its cumulativeness create barriers to competitive entry. This allows a firm to earn the premiums that create market power and allow further innovation to be financed. The model of technological innovation advanced in this thesis has at its core the strategic governance framework of a firm, within which the dynamics of significant new technology, human capital and social processes are catalysed and made productive by differentiated technological learning processes. No one type of technological learning applies universally, but rather learning is differentiated by variables such as firm size and structure, the past experience and core competencies of the firm, its human capital stocks, social processes, interactions with the external environment, and a host of market, institutional and technological factors. It is argued that the dynamics of significant new technology, human capital and social processes are fundamental and necessary conditions of technological innovation. Technological learning processes underly and provide a connecting thread that integrates these necessary conditions into a model of technological innovation that can be applied by managers to create and sustain competitive advantage. Technological learning both shapes and is shaped by the human capital stocks and social processes of a firm. Learning processes give rise to significant new technology, and the dynamics of that technology in turn helps catalyse and gives rise to further learning. The rate and direction of learning and of technological innovation is also driven by the firm's interaction with external sources of ideas and technology. To create competitive advantage through technological innovation business managers must address a firm's strategy, human capital-related assets, social processes and technological learning abilities. Policy managers must ensure that the public technostructure is in place to foster human capital creation within an economy and to facilitate access to new ideas and sources of stimulus.</p>

A Study of Technological Innovation in New Zealand

<p>This thesis addresses the research problem of "what are the key underpinning assets or drivers of technological innovation, and how can they be harnessed to create competitive advantage?" Technological change is an evolutionary process. Research and technological innovation creates knowledge and technology that is irreversible in the sense that inventions can be superseded but not "uninvented". Technological innovation creates knowledge and technology that is cumulative because it lays a platform for further knowledge creation, or sets in place another rung in an ascending ladder of new performance characteristics or properties which are demonstrably superior to their antecedents. In turn, the asset specificity and irreversibility of technology and its cumulativeness create barriers to competitive entry. This allows a firm to earn the premiums that create market power and allow further innovation to be financed. The model of technological innovation advanced in this thesis has at its core the strategic governance framework of a firm, within which the dynamics of significant new technology, human capital and social processes are catalysed and made productive by differentiated technological learning processes. No one type of technological learning applies universally, but rather learning is differentiated by variables such as firm size and structure, the past experience and core competencies of the firm, its human capital stocks, social processes, interactions with the external environment, and a host of market, institutional and technological factors. It is argued that the dynamics of significant new technology, human capital and social processes are fundamental and necessary conditions of technological innovation. Technological learning processes underly and provide a connecting thread that integrates these necessary conditions into a model of technological innovation that can be applied by managers to create and sustain competitive advantage. Technological learning both shapes and is shaped by the human capital stocks and social processes of a firm. Learning processes give rise to significant new technology, and the dynamics of that technology in turn helps catalyse and gives rise to further learning. The rate and direction of learning and of technological innovation is also driven by the firm's interaction with external sources of ideas and technology. To create competitive advantage through technological innovation business managers must address a firm's strategy, human capital-related assets, social processes and technological learning abilities. Policy managers must ensure that the public technostructure is in place to foster human capital creation within an economy and to facilitate access to new ideas and sources of stimulus.</p>

Applying Endogenous Learning Models in Energy System Optimization

Conventional energy production based on fossil fuels causes emissions that contribute to global warming. Accurate energy system models are required for a cost-optimal transition to a zero-emission energy system, which is an endeavor that requires a methodical modeling of cost reductions due to technological learning effects. In this review, we summarize common methodologies for modeling technological learning and associated cost reductions via learning curves. This is followed by a literature survey to uncover learning rates for relevant low-carbon technologies required to model future energy systems. The focus is on (i) learning effects in hydrogen production technologies and (ii) the application of endogenous learning in energy system models. Finally, we discuss methodological shortcomings of typical learning curves and possible remedies. One of our main results is an up-to-date overview of learning rates that can be applied in energy system models.