Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Machine learning

Building Leadership Effectiveness This program encourages leaders to develop practices that transform values into action, vision into realities, obstacles into innovations, and risks into rewards. Participants will be introduced to the five practices of exemplary leadership: modeling the way, inspiring a shared vision, challenging the process, enabling others to act, and encouraging the heart Coaching & Communicating for Performance Coaching & Communicating for Performance is a highly interactive program that will give supervisors and managers the opportunity to build skills that will enable them to share expectations and set objectives for employees, provide constructive feedback, more effectively engage in learning conversations, and coaching opportunities. Skillful Conflict Management for Leaders As a leader, it is important to understand conflict and be effective at conflict management because the way conflict is resolved becomes an integral component of our university’s culture. This series of conflict management sessions help leaders learn and put into practice effective strategies for managing conflict.

기독교 사역과 Leadership

The Social Psychology of Organizations.

Ethical leadership: A social learning perspective for construct development and testing

\"What are your assumptions (implicit as well as explicit) about the most effective way to manage people?\" So began Douglas McGregor in this 1960 management classic. It was a seemingly simple question he asked, yet it led to a fundamental revolution in management. Today, with the rise of the global economy, the information revolution, and the growth of knowledge-driven work, McGregor's simple but provocative question continues to resonate-perhaps more powerfully than ever before. Heralded as one of the most important pieces of management literature ever written, a touchstone for scholars and a handbook for practitioners, The Human Side of Enterprise continues to receive the highest accolades nearly half a century after its initial publication. Influencing such major management gurus such as Peter Drucker and Warren Bennis, McGregor's revolutionary Theory Y-which contends that individuals are self-motivated and self-directed-and Theory X-in which employees must be commanded and controlled-has been widely taught in business schools, industrial relations schools, psychology departments, and professional development seminars for over four decades. In this special annotated edition of the worldwide management classic, Joel Cutcher-Gershenfeld, Senior Research Scientist in MIT's Sloan School of Management and Engineering Systems Division, shows us how today's leaders have successfully incorporated McGregor's methods into modern management styles and practices. The added quotes and commentary bring the content right into today's debates and business models. Now more than ever, the timeless wisdom of Douglas McGregor can light the path towards a management style that nurtures leadership capability, creates effective teams, ensures internal alignment, achieves high performance, and cultivates an authentic, value-driven workplace--lessons we all need to learn as we make our way in this brave new world of the 21st century.

The Human Side of Enterprise.

In this paper the objectives of a new international research project that focuses on the perception of leadership across cultures will be presented. The definition of leadership will be discussed in relation to cross-cultural leadership research. The ideas and theory on which the project is based will be introduced along with several of the hypotheses the project is designed to test. Besides testing the general hypotheses, results obtained in the GLOBE study can also be used for a more focused comparison between two countries. In this paper, differences in preferred leadership attributes and national culture dimensions in The Netherlands and Poland are presented. A total of 287 Dutch managers from six organizations and 277 Polish managers from six organizations filled out questionnaires. The results indicate that Dutch and Polish cultures differ strongly on power distance, uncertainty avoidance and future orientation. Regarding preferred attributes for outstanding leadership, Polish respondents score especially high on administrative skills, vision, and diplomacy, whereas Dutch managers emphasize integrity, inspirational behavior and vision. Polish respondents are also less negative about autocratic leadership.

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Dutch and Polish perceptions of leadership and culture: The globe project

In most modern workplaces it is not enough for employees to react and adapt to changes in their environment; rather, they need to plan ahead and prepare for potential threats and dangers in the future by taking the initiative today. Research has shown that in general, engaging in proactive behaviour comes with beneficial results. But sometimes employee proactivity may also lead to negative (side) effects, such as increased stress. Employees therefore need to consider the trade-offs between rewards and potential costs of proactive behaviour at work.

Being proactive at work - blessing or bane?

With the ageing global population the demand for nursing jobs and the requirements for complex care provision are increasing. In consequence, nursing professionals need to be ready to adapt, obtain variety of skills and engage in career self-management. The purpose of this paper is to investigate individual, micro-level, resources and behaviors that can facilitate matching processes between nursing professionals and their jobs.,A survey-based study was conducted among 314 part-time and full-time nursing professionals in Hungary.,Consistent with the career construction theory, this study offers evidence on career adaptability as a self-regulatory resource that might stimulate nurses’ adaptation outcomes. Specifically, it demonstrates positive relationships between adaptive readiness (proactive personality and conscientiousness), career adaptability, adapting behaviors (career planning and proactive skill development) and adaptation outcomes (employability and in-role performance).,The cross-sectional design limits causal inference. Relatively small sample of full-time professionals for whom supervisory-ratings were obtained yields the need of further replication.,Stimulating development of nurses’ career adaptability, career planning, and proactive skill development can contribute to sustainable career management. It can facilitate the alignment of nurses to performance requirements of their current jobs, preventing individual person-job mismatch.,Zooming into the context of nursing professionals in Hungary, the study elucidates the understudied link between adaptivity and adapting responses and answers the call for more research that employs other-ratings of adaptation outcomes. It demonstrates the value of career adaptability resources for nurses’ employability and in-role performance.

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Antecedents and outcomes of Hungarian nurses’ career adaptability

Taking an interdisciplinary approach, this volume focuses on the trust processes between people within organizations, with an emphasis on empirical studies. Rational foundations and psychological motivations for trust are taken into account through conceptual and empirical chapters. The authors begin by summarizing a number of key elements from the literature including how trust develops in time, and how its development is affected by social-psychological phenomena. This includes the notion of ‘framing': the interpretive context in which actions are perceived and evaluated. A conceptual framework is then used to analyse trust and power in the internal relationships of the organization. The contributors take up this issue in an evolutionary analysis of competition between trust and cheating.

Trusting others in organizations: leaders, management and co-workers

In knowledge-intensive services innovative behaviour of co-workers is a critical success factor. In sectors like consultancy, research and architecture the nature of the work implies that projects are never alike. Innovative behaviour means that co-workers generate ideas for better and/or different products, services or working methods, and strive for implementing such changes. By carrying out certain leadership styles, entrepreneurs are able to boost innovative behaviour of their employees. This study presents an overview of innovation-enhancing leadership styles.

Deanne N. Den Hartog

Papers

Dutch and Polish perceptions of leadership and culture: The globe project

Being proactive at work - blessing or bane?

Antecedents and outcomes of Hungarian nurses’ career adaptability

Trusting others in organizations: leaders, management and co-workers

Leadership as a determinant of innovative behaviour