Fostering creative problem solving and collaborative skills through impromptu design in engineering design courses

There is an increasing recognition of the importance for universities to develop curricula that fosters creative problem solving and collaborative teamwork skills as a key element of an engineering degree program. The historical emphasis on convergent thinking skills that currently dominates engineering tertiar y education is seen as an imbalanced response to the skill sets necessary for design innovation, both individually and within sophisticated multidisciplinary teams, just when they are needed most. Such skills are highly valued by employers, and their development needs to be actively encouraged and facilitated by engineering educators. The role that synthesis or creativity plays in design is a much overlooked aspect in engineering education largely due to the perception that there is a lack of scientific rigour associated with divergent thinking and collaborative skills. Over the past three years a learning activity referred to as ‘Impromptu Design’ has been utilised in a first year design course at the University of New South Wales Mechanical and Manufacturing Engineering degree program. Impromptu Design provides a first concrete experience in an implementation of Kolb’s Experiential Learning Model as a major pedagogical approach for the design course. The objectives of this approach include the development o f divergent thinking skills in engineering students and the improvement of the first year experience in enjoyment of the intellectual excitement and challenge of studying in their field. Impromptu design competitions are a very effective starting point in the model for engaging students in problem identification, formulation, solution and group work, as well as providing an opportunity for students to develop a sense of identity with the discipline and meet other students in the course

Integration schemes and decomposition modes in complex problem solving

Integrated product development requires that decomposition and integration schemes be congruent and in harmony with each other. This harmony marks a complex and large scale product development project with success. In domain of problem solving one needs to resort to a priori knowledge about problem structure indicating the problem’s underlying couplings/complexity. Here, we refer to the problem structure as the self map of the system. Usually for large scale problems the self needs to be decomposed for tractability purposes. The structure of the problem after decomposition is the real structure to be dealt with. In this paper we measure the complexity of systems before and after decomposition. We refer to complexity of the system/problem before decomposition as self complexity and that of system after decomposition as real complexity. It is shown that real complexity cannot be less than self complexity regardless of the decomposition type, and therefore decomposition does not reduce the overall complexity of problem. Also it is shown that by using real complexity measure of decomposed system, weak and strong emergence can be detected in the system. This would have important implications in problem classification and choosing the right design process that is in congruence with complexity of the problem

Exploiting non-dominance in multi agent systems: An artificial immune algorithm for distributed and complex Problem solving environments

An ideal Multi Agent System is flat and has no dominant hierarchy. Multi agent computational and problem solving environments have been advocated for their ability to deliver overall solutions that are innovative and creative. There is however a significant threat to the coherence of Multi Agent Systems; chaos. This paper poses a new vision to the control and immunisation of the Multi Agent Systems against chaos. Employing a complexity measure of the problem and its lower and upper bounds, and monitoring the complexity of the problem solving agents’ interactions, we propose the holistic control of the Multi Agent Systems that leads to immunisation of the system against chaos. The control however is not central and appears in the form of the agents’ common knowledge and determines their tendency to proactively communicate

Analysing the learning pathways of students in a large flipped engineering course

Recent advancements in educational technologies (learning management systems, online discussion forums, peer-learning tools) coupled with new methods of course delivery (e.g. blended, flipped, MOOCs) provide significant opportunities for universities to deliver challenging, high quality, yet engaging curriculum for students. In this paper, we examine the variations and similarities of student's approaches to learning (learning pathways) by examining how well they performed in a large (N ~ 1000 student) first year engineering flipped classroom. The analysis focused on student's performance in their assessment (formative and summative) as well as their online interaction with a range of tools purposely built to support students through peer learning and acquisition of resources and expertise. Analysis using k-means clustering reveals that students do in fact adopt a variety of successful pathways through the course. The unique aspects of this work lie in the use of analytics algorithms that whilst perhaps routinely utilised in data mining, are not as well utilised in better understanding patterns (successful or otherwise) of student interactions within a technology enhanced active learning environment that integrates theory with engineering practice