Qualitative and quantitative assessment : on generalizability of cognitive computational models
- Hedayati Zafarghandi, Shekoofeh
- [University Park, Pennsylvania] : Pennsylvania State University, 2019.
- Physical Description:
- 1 electronic document
- Additional Creators:
- Wyble, Brad
- Restrictions on Access:
- Open Access.
- In this project, I proposed a standardized procedure to test the generalizability of computational cognitive models with respect to a novel dataset. The proposed algorithm was initially tested on a toy model example, and then was applied to a real behavioral dataset using the attentional blink. Despite previous studies examining models against novel data mostly through quantitative approaches, this project emphasizes on the importance of including qualitative features to the quantitative measures. The results of the study indicated that combining qualitative features with quantitative measures will provide information about a models performance based on various parameter values, and that the theoretical goals represented by qualitative features are maintained throughout the searching process when these two criteria (quantitative and qualitative) are integrated.
- Other Subject(s):
- Dissertation Note:
- M.S. Pennsylvania State University 2019.
- Technical Details:
- The full text of the dissertation is available as an Adobe Acrobat .pdf file ; Adobe Acrobat Reader required to view the file.
View MARC record | catkey: 27983952