Assessing student collaboration and learning in medical engineering from the perspectives of structures, behaviors, and function

Learning in biomedical engineering is highly interdisciplinary: students need to integrate concepts between engineering and life sciences, and be able to design and develop technologies with physiological considerations. In this study, biomedical engineering students’ artifacts were analyzed in detail according to the structure-behavior-framework (SBF) framework. The SBF framework has been investigated by educational researchers and learning scientists; in particular, the behavioral and functional dimensions were proved to be related to a sophisticated level of understanding of complex systems. Existing research results also indicate that experts (or expert-like learners) show a deeper understanding of the behavioral and functional aspects of systems. In the current study, a 5- level scale comprising structural, behavioral, andfunctional dimensions of integrated learning was constructed to assess student learning in a biomedical engineering project course. Our results indicate that high achievers and low achievers were different in the behavioral and functional dimensions. The results also indicate significant relationships between behavioral and functional dimensions of learning and students’ final course performance. These findings align with existing results in cognitive science and learning sciences on expert-novice differences, which help connecting engineering educational inquiries to the rich body of literature and findings in human learning

Assessing integrative learning among engineering students using a structure-behavior-function framework

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The proliferation of functions: Multiple systems playing multiple roles in multiple supersystems

AbstractWhen considering a system that performs a role, it is often stated that performing that role is afunctionof the system. The general form of such statements is that “the function ofSisR,” whereSis the functioning system andRis the functional role it plays. However, such statements do not represent how that single function was selected from many possible alternatives. This article renders those alternatives explicit by revealing the other possible function statements that might be made when eitherSorRis being considered. In particular, two forms of selection are emphasized. First, when we say “the function ofSisR,” there are typically many systems other thanSthat are required to be in operation for that role to be fulfilled. The functioning system,S, does not perform the role,R, all by itself, and those systems that supportSin performing that role might also have been considered as functioning. Second, when we say, “the function ofSisR,” there are typically many other roles thatSplays apart fromR, and those other roles might also have been considered functional. When we make function assignments, we select both the functioning system,S, and the functional role,R, from a range of alternatives. To emphasize these alternatives, this article develops a diagrammatic representation of multiple systems playing multiple roles in multiple supersystems.This work  was partly supported by an Early Career Fellowship (EP/K008196/1) from the  UK’s Engineering and Physical Sciences Research Council (EPSRC) and by an  Interdisciplinary Fellowship in Philosophy (Crausaz Wordsworth 2013/14)  from the Centre for Research in the Arts, Social Sciences and Humanities  (CRASSH) at the University of Cambridge. This is the author accepted manuscript. The final version is available at http://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=9520930&fileId=S0890060414000626

Multi-level analysis strategy to make sense of concept maps

Making sense of concept maps is an ongoing challenge for the concept mapping community. This paper introduces a multi-level analysis strategy by combining quantitative and qualitative methods to triangulate changes in students’ concept maps. Quantitative analysis includes overall, selected, and weighted propositional analysis using a knowledge integration rubric (Linn, 2000) as well as network analysis to describe changes in network density and prominence of selected concepts. Research suggests that scoring only selected propositions can be more sensitive to indicate conceptual change because it focuses on key concepts of the map. Qualitative analysis includes topographical analysis methods to describe the overall geometric structure of the map and an analysis of link types. This paper suggests that a combination of quantitative and qualitative analysis methods can capture different aspects of concept maps and provide a rich description of changes in students' understanding of complex topics

Function Based Design-by-Analogy: A Functional Vector Approach to Analogical Search

Design-by-analogy is a powerful approach to augment traditional concept generation methods by expanding the set of generated ideas using similarity relationships from solutions to analogous problems. While the concept of design-by-analogy has been known for some time, few actual methods and tools exist to assist designers in systematically seeking and identifying analogies from general data sources, databases, or repositories, such as patent databases. A new method for extracting functional analogies from data sources has been developed to provide this capability, here based on a functional basis rather than form or conflict descriptions. Building on past research, we utilize a functional vector space model (VSM) to quantify analogous similarity of an idea's functionality. We quantitatively evaluate the functional similarity between represented design problems and, in this case, patent descriptions of products. We also develop document parsing algorithms to reduce text descriptions of the data sources down to the key functions, for use in the functional similarity analysis and functional vector space modeling. To do this, we apply Zipf's law on word count order reduction to reduce the words within the documents down to the applicable functionally critical terms, thus providing a mapping process for function based search. The reduction of a document into functional analogous words enables the matching to novel ideas that are functionally similar, which can be customized various ways. This approach thereby provides relevant sources of design-by-analogy inspiration. As a verification of the approach, two original design problem case studies illustrate the distance range of analogical solutions that can be extracted. This range extends from very near-field, literal solutions to far-field cross-domain analogies.National Science Foundation (U.S.) (Grant CMMI-0855326)National Science Foundation (U.S.) (Grant CMMI-0855510)National Science Foundation (U.S.) (Grant CMMI-0855293)SUTD-MIT International Design Centre (IDC

Integrating post-manufacturing issues into design and manufacturing decisions

An investigation is conducted on research into some of the fundamental issues underlying the design for manufacturing, service and recycling that affect engineering decisions early in the conceptual design phase of mechanical systems. The investigation focuses on a system-based approach to material selection, manufacturing methods and assembly processes related to overall product requirements, performance and life-cycle costs. Particular emphasis is placed on concurrent engineering decision support for post-manufacturing issues such as serviceability, recyclability, and product retirement

Model-based reasoning: using visual tools to reveal student learning

Luckie D, Harrison SH, Ebert-May D. Model-based reasoning: using visual tools to reveal student learning

From modularity to emergence: a primer on the design and science of complex systems

Electrical networks, flocking birds, transportation hubs, weather patterns, commercial organisations, swarming robots... Increasingly, many of the systems that we want to engineer or understand are said to be ‘complex’. These systems are often considered to be intractable because of their unpredictability, non-linearity, interconnectivity, heterarchy and ‘emergence’. Such attributes are often framed as a problem, but can also be exploited to encourage systems to efficiently exhibit intelligent, robust, self-organising behaviours. But what does it mean to describe systems as complex? How do these complex systems differ from the more easily understood ‘modular’ systems that we are familiar with? What are the underlying similarities between different systems, whether modular or complex? Answering these questions is a first step in approaching the design and science of complexity. However, to do so, it is necessary to look beyond the specifics of any particular system or field of study. We need to consider the fundamental nature of systems, looking for a common way to view ostensibly different phenomena. This primer introduces a domain-neutral framework and diagrammatic scheme for characterising the ways in which systems are modular or complex. Rather than seeing modularity and complexity as inherent attributes of systems, we instead see them as ways in which those systems are characterised by those who are interested in them. The framework is not tied to any established mode of representation (e.g. networks, equations, formal modelling languages) nor to any domain-specific terminology (e.g. ‘vertex’, ‘eigenvector’, ‘entropy’). Instead, it consists of basic system constructs and three fundamental attributes of modular system architecture, namely structural encapsulation, function-structure mapping and interfacing. These constructs and attributes encourage more precise descriptions of different aspects of complexity (e.g. emergence, self-organisation, heterarchy). This allows researchers and practitioners from different disciplines to share methods, theories and findings related to the design and study of different systems, even when those systems appear superficially dissimilar

Functional modeling through energy flow diagrams for novice engineering design students

Functional Modeling through Energy Flow Diagrams for Novice Engineering Design Students By Sadhan Sathyaseelan, MSE The University of Texas at Austin, 2015 SUPERVISOR: Richard Crawford The UTeachEngineering program from The University of Texas at Austin is currently developing a high school engineering curriculum that emphasizes design, project-based learning, and development of engineering habits of mind. One module in the curriculum uses reverse engineering of an electromechanical device to teach functional modeling, among other design methods and techniques. Experienced engineers think in terms of the functions – what a product or system must do – before they determine what it will be in its physical form. This is an abstract way of thinking that is commonly taught to engineering undergraduate students, but can be difficult for high school students to grasp. To assist novice engineers (both high school students and undergraduates), a new approach has been developed and evaluated. The Energy Flow Diagram (EFD) focuses on modeling and documenting the energy flow and transformations in the product or system. Energy conversions are prevalent in most products that are feasible for high school students to reverse engineer, and we hypothesize that the results of energy conversions are evident in the behavior of these products. In this paper, we describe the EFD and the materials developed to support its teaching. The EFD method was piloted with an assortment of students from different majors and year of study in the undergraduate level. A pre/post-test was conducted to evaluate any increase in functional thinking among novice design engineers. It was found that the tool was much simpler to understand and implement, and also provided some insights for product redesign opportunities that are similar to the current method of teaching functional modeling.Mechanical Engineerin