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A new stochastic load forecasting model to predict load growth on radial feeders has been developed. Present methods of making such predictions have no underlying a priori model on which to rely. This paper summarizes an attempt to apply developmental models to the load growth prediction problem. A parameter study is described which suggests the relative importance of the model's parameters. Using actual data obtained from a utility company, forecasts are compared with network growth.

This paper discusses the use of stochastic models based on the Box‐Jenkins modeling methodology to determine the future electrical loads. The developed forecasting models have been applied successfully by using the electrical load data provided by the Oklahoma Gas and Electric Company.

Games are an effective teaching and classroom training tool, since they allow students to practise real‐life events. In the area of project management, most games focus on the planning phase of a project. The current paper aims to describe a new game, called PEG – Project Execution Game. The uniqueness of this game is its focus on real world problems during the project's execution.

The Project Execution Game provides the “players” with a set of realistic, but unexpected events that occur during a project, in order to enhance their problem‐coping capabilities and decision‐making skills as well as hone their general reactions. The game is designed for either one or several teams competing among themselves. The game's validity was tested on 185 undergraduate students in their advanced project management course. Statistical results about the simulation's contributions are presented in relation to several aspects of project management.

The conclusion from the study is that a game is an effective tool for teaching the unstructured area of project execution, and gives the student a taste of real‐life experience.

The Project Execution Game can be implemented with students in project management training sessions. With this game, the students gain more practical relevant experience, as compared to alternative teaching techniques. Furthermore, the game can be used in organizational training to improve project managers' techniques and experience in reacting to unexpected events. Finally, it can also be used with project managers practising before the actual execution of a big project.

This paper suggests effective and interesting ways of teaching project management in order to better train project managers. By simulating realistic competitive conditions, the concepts learned and solutions generated in the classroom can be transferred to the outside business environment.

The purpose of this research paper is to explore the interrelations between success in the Business Games course and other MSc courses, and the parameters that influence success in managing firms in business games.

The research sample was comprised of graduate students from the Management of Technology faculty at Holon Institute of Technology. They study courses in the program, including the Business Games course. Special business game software, named Decision Makers, was used for the analyses. Statistical analyses of the interrelations among different program courses cover the main purpose. After defining five success criteria, statistical analyses of success and failure are presented.

In this course, success was generally uncorrelated with other courses. The reason for this was probably due to its project‐based learning (PBL) environment. The study shows that students tend to reduce their efforts across time and improve their performance, due to the “learning curve”. Analysis of the results shows that when teams overused the simulation runs, they do not analyze their situation, but rather prefer the “trial and error” method.

The present study provides results about the importance of training managers through using the business game simulator.

Using PBL is very exiting for those students who have difficulties in classroom studies. By using PBL, these students rapidly improve their management skills.

Computers and computer‐assisted instruction are being used with increasing frequency in the area of health science student education, yet students’ attitudes towards the use of e‐learning technology and computer‐assisted instruction have received limited attention to date. The purpose of this study was to investigate the significant predictors of health science students’ attitudes towards e‐learning and computer‐assisted instruction. All students enrolled in health science programmes (n=2885) at a large multi‐campus Australian university in 2006‐2007, were asked to complete a questionnaire. This included the Online Learning Environment Survey (OLES), the Computer Attitude Survey (CAS), and the Attitude Toward Computer‐Assisted Instruction Semantic Differential Scale (ATCAISDS). A multiple linear regression analysis was used to determine the significant predictors of health science students’ attitudes to e‐learning. The Attitude Toward Computers in General (CASg) and the Attitude Toward Computers in Education (CASe) subscales from the CAS were the dependent (criterion) variables for the regression analysis. A total of 822 usable questionnaires were returned, accounting for a 29.5 per cent response rate. Three significant predictors of CASg and five significant predictors of CASe were found. Respondents’ age and OLES Equity were found to be predictors on both CAS scales. Health science educators need to take the age of students and the extent to which students perceive that they are treated equally by a teacher/tutor/instructor (equity) into consideration when looking at determinants of students’ attitudes towards e‐learning and technology.

This study compared the gentrification processes in Cihangir and Tarlabasi. The dynamics of the gentrification process in Cihangir is compared with the vastly different gentrification process in Tarlabasi. Interpretations of gentrification are also included in this paper.

The study analyzed the dynamics of the gentrification process in Cihangir, Istanbul (Turkey) to determine the extent of change during the process. Characterization of the Cihangir neighborhood, which distinguishes Cihangir from other gentrified urban areas, is another aspect of this study. The transformation of Cihangir is currently underway; it involves the revolution and renovation of land and buildings, which is known as gentrification. The gentrification process in Cihangir is affected by socio-economic and socio-cultural transformations. This paper examines gentrification in the Cihangir neighborhood, which has occurred spontaneously and supports the perpetuation of social diversity, which occurs in many urban areas. Although Istanbul’s Tarlabasi region exhibits geophysical characteristics that resemble the geophysical characteristics of Cihangir, Tarlabasi is affected by a completely different gentrification process, which is known as planned gentrification.

In the context of this study, scholars question whether gentrification is “erasing the social geography of urban land and unique architectural pattern,” or if gentrification represents “the upgrading and renaissance of the urban land.” (Smith, 1996)

There are a large number of interdependent risk factors in complex project. Risk response strategy without considering risk correlation cannot achieve good risk response. Therefore, the purpose of this paper is to propose a risk response strategy selection model considering risk correlation based on the grey K-shell algorithm.

This paper mainly focuses on the measurement of two aspects of risk factors. One is the ability of the risk factors to influence other risk factors, another is the degree affected by other risk factors. Both of the above are measured by the grey K-shell algorithm improved in this paper, and the weights of these are used for the constructing of risk response strategy selection model.

The risk response strategy considering risk relevance is more effective than the risk response strategy without considering risk relevance. Also, results indicate that as the risk response budget increases the risk response effect also increases, and the increasing trend is weakens. The relative gap between the effect of response strategies considering risk relevance and the strategy without considering risk relevance increases first and, then, decreases with the increase of budget.

The results of this paper demonstrate that the risk response strategy considering risk relevance is more effective than not considering risk relevance. The approach presented in this paper can guide project managers’ risk decisions and may also help to find the best risk response budget.

The purpose of this paper is to provide a systematic classification for frameworks, methods, and models of in-project quantitative risk analysis (IQRA) for the last 30 years.

An extensive literature review is conducted to identify pertinent IQRA works. Identified IQRA frameworks/methods/models are then classified on the basis of commonalities in key attributes and assumptions. Linkages between each category of IQRAs and dimensions of complexity are also observed.

Around 70 key publications on IQRAs are identified. Major attributes for each work are described. Five distinct categories of IQRAs emerge with unique linkages to complexity dimensions. An analytical framework in the form of a matrix is presented to illuminate evolution on modeling characteristics and to indicate a relationship between respective category and dimensions of project complexity.

The research coverage is intended to be comprehensive but it is by no means exhaustive. This study highlights research opportunities in IQRAs and the possible extension toward in-project quantitative complexity analysis (IQCA).

The proposed matrix provides guidance to practitioners to select the appropriate category of IQRAs for a specific project complexity type in a contingency fashion. The study highlights lessons from development and utilization of IQRAs. Outstanding issues from IQRAs are discussed to avoid similar drawbacks for IQCAs.

This study provides an original framework/matrix to classify extant works in IQRAs. It also establishes an association between IQRAs and the emerging conceptual works of complexity.

Most university students, if not all, develop a preconception about any academic course before taking it. This preconception undeniably affects students’ performance by influencing their motivation. As a result, learning can be minimized. The purpose of this paper is to investigate the evolution of students’ preconception about the difficulty of an engineering course – taught by the same instructor – for a period of seven semesters by analyzing the results of survey questionnaire completed at the beginning of every semester. This approach allows the instructor to assess students’ preconception that is built by former students’ feedback and hence control the impact on students’ motivation which influences their learning performance.

By analyzing the surveys’ results, the instructor gets a close idea about how the course is perceived. When students harbor misconceptions that constitute difficult barriers to learning, it becomes necessary to take action like adjusting the way of teaching the corresponding course’s content, or ultimately changing the course instructor for a couple of semesters.

The adopted survey-based strategy implicitly helps the instructor to correct inaccurate preconceptions before they become crystallized misconceptions, while in case of a very positive preconception, one can continue to enhance the course level with even more challenging evaluations (e.g. exams). However, in case of a persistent misconception, a midterm survey would further help the instructor to better adjust the way the course is taught by objectively considering the obtained inputs from a considered C/D/S set (i.e. continue doing what was helpful/do start doing what would be beneficial/stop doing what is not working).

To the best of the author’s knowledge, no study has investigated the evolution of – or at least – students’ preconception built by former students’ feedback about the difficulty of a course despite its direct influence on students’ motivation and hence on students’ performance, thus filling an important gap in the literature. Indeed, one general positive aspect of students’ preconception research is the attention it has brought regarding the absolute necessity for teachers and researchers to be well grounded in both content knowledge and pedagogical content knowledge.