| dc.contributor | 應數系 | - |
| dc.creator (作者) | Wu, Berlin | - |
| dc.creator (作者) | 吳柏林 | zh_TW |
| dc.creator (作者) | Lin, Y.-H. | en_US |
| dc.date (日期) | 2007-01 | - |
| dc.date.accessioned | 13-Jul-2015 17:12:15 (UTC+8) | - |
| dc.date.available | 13-Jul-2015 17:12:15 (UTC+8) | - |
| dc.date.issued (上傳時間) | 13-Jul-2015 17:12:15 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/76552 | - |
| dc.description.abstract (摘要) | The evaluation of public consensus is an important issue in the quantitative research. Most of research methods, like the survey or questionnaire, are to ask task-takers to answer their thinking in binary logic and provide a single answer on questions. Most researchers usually adopt statistical computations in traditional approaches to express public consensus. However, this data analysis ignores the fuzzy thinking perceived in human logic and recognition without considerations on human thinking. Fuzzy theory provides the foundation of multi-logic which is beyond the limitations of binary logic. Thus, fuzzy theory should be more proper to express human thinking based on membership function and fuzzy statistical analysis. In this paper, we will provide the definitions, proofs and properties of fuzzy mode. In addition to discussing these characteristics of fuzzy mode, the comparisons and applications of traditional model and fuzzy mode are discussed. These empirical data sets are to measure public consensus in educational survey. It is concluded that fuzzy mode should be proper to express human thinking. Finally, suggestions and recommendations for future research and advanced issues are presented. | - |
| dc.format.extent | 176 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | WSEAS Transactions on Mathematics, 6(1), 145-150 | - |
| dc.subject (關鍵詞) | Formal logic; Fuzzy sets; Membership functions; Statistical methods; Students; Educational measurement; Fuzzy mode; Traditional mode; Behavioral research | - |
| dc.title (題名) | The comparisons and applications of traditional mode and fuzzy mode in quantitative research | - |
| dc.type (資料類型) | article | en |
