| id |
ecaade2024_85 |
| authors |
Casakin, Hernan; Sopher, Hadas; Anidjar, Or H.; Gero, John S. |
| year |
2024 |
| title |
A Data-Driven NLP Approach to Analyzing Framing and Reframing in Design Protocols |
| source |
Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 547–556 |
| doi |
https://doi.org/10.52842/conf.ecaade.2024.2.547
|
| summary |
This study introduces a novel data-driven approach to quantitatively characterize and measure framing and reframing (F-RF) behaviors during design problem-solving. F-RF are cognitive processes which shape problem understanding and solution development in design. Quantitative measurement methods for F-RF remain largely unexplored. The proposed approach utilizes protocol analysis combined with Natural Language Processing (NLP) algorithms to track the occurrences and re-occurrences of design concepts expressed verbally while designing. Specifically, NLP algorithms are employed to identify F-RF, enabling the systematic tracking of F-RFs and their corresponding semantic values. By calculating the semantic value of concepts and frames, the approach enables determining how a concept and a frame differed from the previous occurrences. A case study of an architect and a student demonstrates this data-driven approach. The proposed methodology holds potential for the development of systems capable of providing real-time feedback to students and professional designers, supporting and enhancing their framing skills during the design process. |
| keywords |
Data-driven approach, Natural Language Processing (NLP), Design concept, Design problem-solving, Framing and reframing |
| series |
eCAADe |
| email |
|
| full text |
 file.pdf (470,568 bytes) |
| references |
Content-type: text/plain
|
| last changed |
2024/11/17 22:05 |
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