Georgiev, G., & Georgiev, D. (2019). Semantic Analysis Approach to Studying Design Problem Solving. Proceedings of the Design Society: International Conference on Engineering Design, 1(1), 1823-1832. doi:10.1017/dsi.2019.188
Semantic analysis approach to studying design problem solving
|Author:||Georgiev, Georgi V.1; Georgiev, Danko D.2|
1Center for Ubiquitous Computing, University of Oulu
2Institute for Advanced Study, Varna, Bulgaria
|Online Access:||PDF Full Text (PDF, 0.7 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2019100230818
|Publish Date:|| 2019-10-02
To 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.
Proceedings of the Design Society. International Conference on Engineering Design
|Pages:||1823 - 1832|
Proceedings of the Design Society: International Conference on Engineering Design
International Conference on Engineering Design
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
113 Computer and information sciences
222 Other engineering and technologies
520 Other social sciences
The authors would like to thank Dr. Robin Adams (Purdue University) for the provided access to the DTRS10 dataset under the signed data-use agreement. This research has been partially financially supported by Academy of Finland 6Genesis Flagship (grant 318927).
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
© The Author(s) 2019. This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.