scholarly journals SEMANTIC ANALYSIS OF ENGINEERING DESIGN CONVERSATIONS

2020 ◽  
Vol 1 ◽  
pp. 1265-1274
Author(s):  
G. V. Georgiev ◽  
D. D. Georgiev
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Information Content ◽  
Real World ◽  
Design Problem ◽  
Semantic Analysis ◽  
Semantic Networks ◽  
Dynamic Semantic ◽  
Time Dynamics ◽  
Problem Solving Process

AbstractTo objectively and quantitatively study transcribed protocols of design conversations, we apply a semantic analysis approach based on dynamic semantic networks of nouns. We examined the applicability of the approach focused on a dynamic evaluation of the design problem solving process in engineering design educational settings. Using a case of real-world case, we show that the approach is able to determine the time dynamics of semantic factors such as level of abstraction, polysemy, information content, and quantify convergence/divergence in engineering design conversations.

scholarly journals Semantic Analysis Approach to Studying Design Problem Solving

2019 ◽  
Vol 1 (1) ◽  
pp. 1823-1832
Author(s):  
Georgi V. Georgiev ◽  
Danko D. Georgiev
Keyword(s):  
Problem Solving ◽  
Design Problem ◽  
Semantic Analysis ◽  
Semantic Networks ◽  
Analysis Approach ◽  
Design Solution ◽  
Lexical Database ◽  
Semantic Approach ◽  
Time Dynamics ◽  
Problem Solving Process

AbstractTo objectively and quantitatively study transcribed protocols of design problem solving conversations, we propose a semantic analysis approach based on dynamic semantic networks of nouns constructed with WordNet 3.1 lexical database. We examined the applicability of the semantic approach focused on a dynamic evaluation of the design problem solving process in educational settings. Using a case of real- world design problem-solving conversations, we show that the approach is able to determine the time dynamics of semantic factors such as level of abstraction, polysemy or information content, and quantify convergence/divergence of semantic similarity in design conversations between students, instructors and real clients. The approach can also be used to evaluate the aforementioned semantic factors for successful and unsuccessful ideas generated in the process of design problem solving, or to assess the effect of external feedback on the developed design solution. The proposed semantic analysis approach allows fast computation of the semantic factors in real time thereby demavonstrating a potential for both monitoring and support of the design problem solving process.

Development of Design Skills Through Employment of Open-Ended Problems

1993 ◽  
Author(s):  
Harvey R. Brock ◽  
Sridhar S. Condoor ◽  
Christian P. Burger
Keyword(s):  
Problem Solving ◽  
Engineering Education ◽  
Real World ◽  
Design Problem ◽  
Design Education ◽  
Solution Strategy ◽  
Inconsistent Information ◽  
Engineering Problems ◽  
Design Skills ◽  
Selection Of

Abstract With the recent increased concern about the design and problem solving needs of U.S. industry, and academia’s inability to address them, there has arisen a desire to incorporate open-ended problems in engineering education. In the initial stages most, if not all, real-world engineering problems are ill-defined, and have several acceptable solutions, i.e. they are open ended. Yet, our students get very little practice in finding solutions for this type of problem. Correcting this weakness in engineering curricula is hampered by misconceptions about, and inexperience with, these types of problems. As a consequence, educators often attempt to modify typical well defined example problems by expanding their scope, but still taking care to insure that the solution domains are closely circumscribed and well defined. The goal of this paper is to illustrate the main features of open-ended problems and their utility in design education. Such problems are characterized by incomplete or inconsistent information, no evident solution strategy, non-unique solutions, and often poorly understood goals. A real-world open ended design problem will be contrasted with its’ typical engineering education counterpart. This paper attempts to provide the necessary insights to aid in the formulation and selection of effective open ended problems for use in engineering education.

Effectiveness of Problem Solving Software in Engineering Conceptual Design

2012 ◽  
Author(s):  
Zbigniew M. Bzymek ◽  
Yang Xu
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Conceptual Design ◽  
Teaching And Learning ◽  
Teaching Effectiveness ◽  
Graduate Courses ◽  
Software Products ◽  
Software Packages ◽  
Problem Solving Process ◽  
The University

The process of generating the most attractive product concepts in engineering design is still one of the greatest challenges of the 21st century. There are several tools for supporting this extremely uncontrollable phase of engineering design. Except for the method, the problem-solving software is the very important tool. One of the most useful methods in teaching and learning, i.e. Brief Theory of Inventive Problem Solving (BTIPS), is discussed in other papers [1], [2], [3] and [4]. This paper is devoted to the software supporting the problem solving process. There is still no software suitable for a completely satisfactory automation of the conceptual design process. However there are some software packages that could be the most helpful in supporting the process and would greatly influence the quality of the final product, especially in cases of contradicting constraints. In this paper some results of the research on the use and effectiveness of Invention Machine (IM™) software products are described. Four packages are discussed and compared: the IM v. 2 for Windows, TechOptimizer v. 3.5, TechOptimizer v. 4.0 and Goldfire v. 6.5. Goldfire v. 6.5 evaluation is still in the process and is not completely finished yet. The first three packages were used in teaching several junior, senior and graduate courses at the University of Connecticut (UConn) for many years. The experience with Goldfire v. 6.5 is comparatively limited. In the research described in this paper the content and the teaching effectiveness of the software packages in teaching were studied. Data from student feedback was evaluated, conclusions were derived. On the basis of this - recommendations for the future use of the software are offered. This paper concentrates on some instrumental software qualities that could be used in teaching of solving problems of industrial products conceptual design. The user’s experience and its connection with the effectiveness of the packages used are discussed in the paper. Conclusions are derived at the end.

DEFINING THE APPROPRIATE COURSE PROJECT FOR FOSTERING THE EXPECTED COGNITIVE COMPETENCIES: EBD APPROACH TO AN ENGINEERING DESIGN COURSE

2018 ◽  
Author(s):  
Amirali Ommi ◽  
Yong Zeng
Keyword(s):  
Engineering Design ◽  
Real World ◽  
Design Problem ◽  
Project Based Learning ◽  
Learning Objectives ◽  
Successful Completion ◽  
Future Directions ◽  
Design Project ◽  
House Design

Project-based learning is an inevitable part of current course curriculums, especially in engineering design courses. Incorporating course projects in curriculums is done for overcoming the lack of students’ familiarity with real-world challenges. Students either acquire or further develop those specific competencies upon successful completion of the course project. Thus, defining an appropriate course project becomes essential. The competencies that are fostered may depend either on the design problem or the project contexts. In this study, we employ an EBD approach to developing a framework for evaluating a course project regarding its fitness to course learning objectives. This framework makes it possible to elicit required competencies for accomplishing a course project and comparing it with the set of competencies in the course learning objectives. A case study of a flying house design project is presented to demonstrate the framework application. The discussion of the proposed framework and future directions to our research are presented at the end.

Design Team Convergence: The Influence of Example Solution Quality

2010 ◽  
Vol 132 (11) ◽  
Author(s):  
Katherine Fu ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Semantic Analysis ◽  
Cognitive Engineering ◽  
Design Solution ◽  
Solution Quality ◽  
Team Members ◽  
Solution Approach ◽  
Over Time

This study examines how engineering design teams converge upon a solution to a design problem and how their solution is influenced by information given to them prior to problem solving. Specifically, the study considers the influence of the type of information received prior to problem solving on team convergence over time, as well as on the quality of produced solutions. To understand convergence, a model of the team members’ solution approach was developed through a cognitive engineering design study, specifically examining the effect of the introduction of a poor example solution or a good example solution prior to problem solving on the quality of the produced solutions. Latent semantic analysis was used to track the teams’ convergence, and the quality of design solutions was systematically assessed using pre-established criteria and multiple evaluators. Introducing a poor example solution was shown to decrease teams’ convergence over time, as well as the quality of their design solution; introducing a good example solution did not produce a statistically significant different effect on convergence compared with the control (with no prior example solution provided) but did lead to higher quality solutions.

Design Team Convergence: The Influence of Example Solution Quality

2009 ◽  
Author(s):  
Katherine Fu ◽  
Jonathan Cagan ◽  
Kenneth Kotovsky
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Semantic Analysis ◽  
Cognitive Engineering ◽  
Design Team ◽  
Design Teams ◽  
Solution Quality ◽  
Team Members ◽  
Common Understanding

This study examines how engineering design teams converge to a common understanding of a design problem and its solution, how that is influenced by the information given to them before problem solving and how it is correlated with quality of produced solutions. To understand convergence, a model of the team members’ representations was sought through a cognitive engineering design study, specifically examining the effect of the introduction of a poor example solution and a good example solution prior to problem solving. Latent Semantic Analysis (LSA) was used to track the teams’ convergence. Introducing a poor example solution was shown to have a slowing effect on teams’ convergence over time and quality of design, while the good example solution was not significantly different than the control (no example solution) in its effects on convergence, but did cause higher quality solutions. This may have implications for design team performance in practice.

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