An Evaluation of Existing On-Line Learning & Teaching Resources for the Socio-Economic Aspects of Sustainable Design, New Perspectives in Design Education

This paper fits into the topic of eco-design education and explores questions related to the modern student’s perspective on design education and how we should consider the curricula from a future perspective. This paper first confirms the state of the art by reviewing the literature on the socio-centric dimension of sustainable design. This will determine the component sections required of a learning and teaching resource which focuses on the implications of human expectations and aspirations for the development of solutions to sustainable design problems

Comparative study of design: application to Engineering Design

A recent exploratory study examines design processes across domains and compares them. This is achieved through a series of interdisciplinary, participative workshops. A systematic framework is used to collect data from expert witnesses who are practising designers across domains from engineering through architecture to product design and fashion, including film production, pharmaceutical drugs, food, packaging, graphics and multimedia and software. Similarities and differences across domains are described which indicate the types of comparative analysis we have been able to do from our data. The paper goes further and speculates on possible lessons for selected areas of engineering design which can be drawn from comparison with processes in other domains. As such this comparative design study offers the potential for improving engineering design processes. More generally it is a first step in creating a discipline of comparative design which aims to provide a new rich picture of design processes

Sustainable design and the design curriculum

This paper reports on an initial study that begins the process of considering how design education should deal with the issue of sustainable design specifically in the context of the education of graduate designers in the fields of product, design engineering and interior design. Consideration is given to the development of the design curriculum and the design process. Further, a number of questions related to shaping the future of design and engineering education are also explored. The question this research seeks to address is whether sustainability, or more specifically sustainable design, should or can be an integral part of engineering/product design programmes or whether it should/or can be developed as a separate design discipline, perhaps as a postgraduate extension to the designer’s core skills set? The research also discusses the difference between, eco-design and sustainable design and the implications of the understanding of this difference for design education

Exemplary Design Research

In this paper, we will look at what role a research program and an interventionist research strategy based on design experiments may play for the advancement of knowledge relevant to design and designers. We suggest the notion of exemplary design research driven by programs and experiments and by this we refer to research based on the explicit formulation of design programs that act as a frame and foundation for carrying out series of design experiments. It is 'exemplary' in the sense that it enables critical dissemination primarily by creating examples of what could be done and how, i.e. examples that both express the possibilities and characteristics of the design program as well as more general suggestions about a certain (change to) design practice

Curriculum Guidelines for Undergraduate Programs in Data Science

The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science