Search

towards engineering education that prepares graduates to work effectively across foreign cultures and customs1-3. The author argues that while this outward focus is important and necessary, there is also a need to focus on preparing graduates for cultural issues that will arise much closer to home. Identifying, and working with subtle cultural differences that can occur in workplaces, organizations and the community, where the population may initially appear monocultural, presents unique challenges. The way in which one assumes cultural uniformity in a given situation can contribute to the oversimplification of a problem, and subsequently the pursuit of ineffective solutions. In a recent project, the author and colleagues sought to develop educational modules that introduced students, and staff, to strategies for identifying complexities arising from these subtle cultural contrasts and conflicts. In the process, a model for knowledge management by Kurtz and Snowden4 has been identified that neatly frames the way we approach learning and decision making in engineering education and practice. The framework distinguishes the ways in which one perceives a problem in terms of its complexity and the strategies employed to solve it. This paper describes the applications of this framework to engineering education that focuses on developing students' intercultural competency. The way this framework has been used to design learning activities as well as its usefulness for staff training and development are outlined. The author proposes potential applications of this framework to other areas of engineering curricula as a way to embrace complexity in learning and teaching and avoid oversimplifying complicated problems.

Human ecosystems are real-life systems characterized by very strong and longterm interactions between human communities and their environment; as such they constitute an expansion of the ecological concept of ecosystem. According to Stepp and colleagues (2003), human ecosystems not only process matter and energy flows, but - and more specifically - information flows as well. Therefore, they display very specific characteristics due to our ability to communicate and learn from others, creating the conditions for co-evolutionary processes in which chance lends a hand to necessity. Bradbury (2006) argues that, until recently, human beings had been able to adapt to changes and to cope with co-evolution through rather simple heuristics. But human activities have gradually strengthened the links globally between loosely connected environments and societies. More information, more interactions and shorter communication paths tend to create intractable dependencies between events and to generate deeper uncertainties overall

Human ecosystems are real-life systems characterized by very strong and longterm interactions between human communities and their environment; as such they constitute an expansion of the ecological concept of ecosystem. According to Stepp and colleagues (2003), human ecosystems not only process matter and energy flows, but - and more specifically - information flows as well. Therefore, they display very specific characteristics due to our ability to communicate and learn from others, creating the conditions for co-evolutionary processes in which chance lends a hand to necessity. Bradbury (2006) argues that, until recently, human beings had been able to adapt to changes and to cope with co-evolution through rather simple heuristics. But human activities have gradually strengthened the links globally between loosely connected environments and societies. More information, more interactions and shorter communication paths tend to create intractable dependencies between events and to generate deeper uncertainties overall

Many reasons have been offered to explain why software projects fail. Still, software intensive projects often present schedule delays, cost overruns and delivering products with reduced functionality. This paper argues that lack of knowledge is yet another factor that causes projects to under perform, which in turn drives undesirable social behaviour that worsens the situation. Software intensive projects develop solutions highly dependent on software that should satisfy a need. The engineering process to develop such complex solutions comprises of a series of transformations that transform products from one domain into products in another domain, requiring knowledge pertinent to both input and output domains. Complex products call for knowledge that may not be available, is often distributed amongst people and organisations and involves learning and cooperation. The engineering of software intensive systems, in particular, frequently adopts techniques that abstract complexity and hide details that reveal, too late, a lack of knowledge in earlier transformations. When knowledge is not applied as required, distortions propagate throughout transformations producing solutions that will not satisfy the need and require rework that increases costs and delays schedules. Software intensive projects may fail because of lack of technical knowledge to engineer the solution, and lack of management knowledge to recognise and plan for this deficiency. When projects are not performing as expected and interests are at risk, decisions are made within constraints that are unlikely to address the lack of knowledge, which often produces undesirable social behaviour that decreases motivation, discourages learning and cooperation and worsens the situation. The paper concludes proposing the adoption of project specific knowledge and behaviour management to improve the performance of software intensive projects.

Many reasons have been offered to explain why software projects fail. Still, software intensive projects often present schedule delays, cost overruns and delivering products with reduced functionality. This paper argues that lack of knowledge is yet another factor that causes projects to under perform, which in turn drives undesirable social behaviour that worsens the situation. Software intensive projects develop solutions highly dependent on software that should satisfy a need. The engineering process to develop such complex solutions comprises of a series of transformations that transform products from one domain into products in another domain, requiring knowledge pertinent to both input and output domains. Complex products call for knowledge that may not be available, is often distributed amongst people and organisations and involves learning and cooperation. The engineering of software intensive systems, in particular, frequently adopts techniques that abstract complexity and hide details that reveal, too late, a lack of knowledge in earlier transformations. When knowledge is not applied as required, distortions propagate throughout transformations producing solutions that will not satisfy the need and require rework that increases costs and delays schedules. Software intensive projects may fail because of lack of technical knowledge to engineer the solution, and lack of management knowledge to recognise and plan for this deficiency. When projects are not performing as expected and interests are at risk, decisions are made within constraints that are unlikely to address the lack of knowledge, which often produces undesirable social behaviour that decreases motivation, discourages learning and cooperation and worsens the situation. The paper concludes proposing the adoption of project specific knowledge and behaviour management to improve the performance of software intensive projects.

Many reasons have been offered to explain why software projects fail. Still, software intensive projects often present schedule delays, cost overruns and delivering products with reduced functionality. This paper argues that lack of knowledge is yet another factor that causes projects to under perform, which in turn drives undesirable social behaviour that worsens the situation. Software intensive projects develop solutions highly dependent on software that should satisfy a need. The engineering process to develop such complex solutions comprises of a series of transformations that transform products from one domain into products in another domain, requiring knowledge pertinent to both input and output domains. Complex products call for knowledge that may not be available, is often distributed amongst people and organisations and involves learning and cooperation. The engineering of software intensive systems, in particular, frequently adopts techniques that abstract complexity and hide details that reveal, too late, a lack of knowledge in earlier transformations. When knowledge is not applied as required, distortions propagate throughout transformations producing solutions that will not satisfy the need and require rework that increases costs and delays schedules. Software intensive projects may fail because of lack of technical knowledge to engineer the solution, and lack of management knowledge to recognise and plan for this deficiency. When projects are not performing as expected and interests are at risk, decisions are made within constraints that are unlikely to address the lack of knowledge, which often produces undesirable social behaviour that decreases motivation, discourages learning and cooperation and worsens the situation. The paper concludes proposing the adoption of project specific knowledge and behaviour management to improve the performance of software intensive projects.

Many reasons have been offered to explain why software projects fail. Still, software intensive projects often present schedule delays, cost overruns and delivering products with reduced functionality. This paper argues that lack of knowledge is yet another factor that causes projects to under perform, which in turn drives undesirable social behaviour that worsens the situation. Software intensive projects develop solutions highly dependent on software that should satisfy a need. The engineering process to develop such complex solutions comprises of a series of transformations that transform products from one domain into products in another domain, requiring knowledge pertinent to both input and output domains. Complex products call for knowledge that may not be available, is often distributed amongst people and organisations and involves learning and cooperation. The engineering of software intensive systems, in particular, frequently adopts techniques that abstract complexity and hide details that reveal, too late, a lack of knowledge in earlier transformations. When knowledge is not applied as required, distortions propagate throughout transformations producing solutions that will not satisfy the need and require rework that increases costs and delays schedules. Software intensive projects may fail because of lack of technical knowledge to engineer the solution, and lack of management knowledge to recognise and plan for this deficiency. When projects are not performing as expected and interests are at risk, decisions are made within constraints that are unlikely to address the lack of knowledge, which often produces undesirable social behaviour that decreases motivation, discourages learning and cooperation and worsens the situation. The paper concludes proposing the adoption of project specific knowledge and behaviour management to improve the performance of software intensive projects.