This paper is based on the premises that the purpose of engineering education is to graduate engineers who can design, and that design thinking is complex. The paper begins by briefly reviewing the history and role of design in the engineering curriculum. Several dimensions of design thinking are then detailed, explaining why design is hard to learn and harder still to teach, and outlining the research available on how well design thinking skills are learned. The currently most-favored pedagogical model for teaching design, project-based learning (PBL), is explored next, along with available assessment data on its success. Two contexts for PBL are emphasized: first-year cornerstone courses and globally dispersed PBL courses. Finally, the paper lists some of the open research questions that must be answered to identify the best pedagogical practices of improving design learning, after which it closes by making recommendations for research aimed at enhancing design learning.

Engineering Design Thinking, Teaching, and Learning

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Engineering design thinking, teaching, and learning

Product design is a highly involved, often ill-defined, complex and iterative process, and the needs and specifications of the required artifact get more refined only as the design process moves toward its goal. An effective computer support tool that helps the designer make better-informed decisions requires efficient knowledge representation schemes. In today's world, there is a virtual explosion in the amount of raw data available to the designer, and knowledge representation is critical in order to sift through this data and make sense of it. In addition, the need to stay competitive has shrunk product development time through the use of simultaneous and collaborative design processes, which depend on effective transfer of knowledge between teams. Finally, the awareness that decisions made early in the design process have a higher impact in terms of energy, cost, and sustainability, has resulted in the need to project knowledge typically required in the later stages of design to the earlier stages. Research in design rationale systems, product families, systems engineering, and ontology engineering has sought to capture knowledge from earlier product design decisions, from the breakdown of product functions and associated physical features, and from customer requirements and feedback reports. VR (Virtual reality) systems and multidisciplinary modeling have enabled the simulation of scenarios in the manufacture, assembly, and use of the product. This has helped capture vital knowledge from these stages of the product life and use it in design validation and testing. While there have been considerable and significant developments in knowledge capture and representation in product design, it is useful to sometimes review our position in the area, study the evolution of research in product design, and from past and current trends, try and foresee future developments. The goal of this paper is thus to review both our understanding of the field and the support tools that exist for the purpose, and identify the trends and possible directions research can evolve in the future.

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The evolution, challenges, and future of knowledge representation in product design systems

CONCLUSIONS This paper’s theoretical contribution is an emergent educational theory of informed design that identifies key performance dimensions relevant to K–16 engineering and STEM educational contexts. Practical contributions include the Informed Design Teaching and Learning Matrix, which is fashioned to help teachers do informed teaching with design tasks while developing their own design pedagogical content knowledge.

The Informed Design Teaching and Learning Matrix

The bridge between engineering design and cognitive science research is critical to understand the effectiveness of design methods as implemented by human designers. The study reported in this paper evaluates the effects of design fixation in a group of engineering design faculty, and also provides evidence for approaches to overcome design fixation. Three conditions are compared, a control, a fixation group whom were provided with an example solution, and a defixation group whom were also given materials to mitigate their design fixation. Measures include indicators of design fixation and participant perceptions. The study demonstrates that the engineering design faculty show statistically significant evidence of design fixation, but only partially perceive its effects. This study also indicates that design fixation can be mitigated. The group of participants in this study, due to their background in engineering design research and experience with student design teams, was expected to have more accurate perceptions or awareness of design fixation than the typical participant. Understanding the incongruities between participant perceptions and quantitative design outcomes are particularly of interest to researchers of design methods. For this study, clear evidence exists that designers, even those that study and teach design on a regular basis, do not know when they are being influenced or fixated by misleading or poor information. DOI: 10.1115/1.4001110

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A Study of Design Fixation, Its Mitigation and Perception in Engineering Design Faculty

https://www.ecologylab.net/research/publications/ShahVargas-HernandezSmith2002.pdf

Metrics for measuring ideation effectiveness

A number of cognitive skills relevant to design have been identified. Formal methods for evaluating these skills in engineering students are needed. Towards that goal we are developing a battery of standardized tests for the most critical of these skills. These tests are based on research in design thinking, human problem solving, cognitive psychology and psychometrics. Tests for Divergent Thinking, Visual Thinking, Spatial Reasoning, Qualitative Reasoning and Problem Formulation are in various stages of development. This paper describes the procedure and rationale for test development. It involves characterization of design skills in terms of measurable indicators; devising skill measurement instruments (problems, metrics, scales); conducting trials to collect data and evaluation of tests for criterion and construct validity. Beta trials are in progress involving undergraduate and graduate students at multiple universities and engineers in industry. Possible applications of these tests include evaluating students in design classes, forming of balanced design teams that posses skills necessary for a given project and evaluating the effectiveness of design courses and curricula.

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Steve M. Smith

Papers

Metrics for measuring ideation effectiveness

Development of Standardized Tests for Design Skills