期刊論文
| 學年 | 110 |
|---|---|
| 學期 | 1 |
| 出版（發表）日期 | 2021-11-28 |
| 作品名稱 | A Deterministic Learning Algorithm Estimating the Q-Matrix for Cognitive Diagnosis Models |
| 作品名稱（其他語言） | |
| 著者 | Mengta Chung |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | Mathematics 9(23), p.3062 |
| 摘要 | The goal of an exam in cognitive diagnostic assessment is to uncover whether an examinee has mastered certain attributes. Different cognitive diagnosis models (CDMs) have been developed for this purpose. The core of these CDMs is the Q-matrix, which is an item-to-attribute mapping, traditionally designed by domain experts. An expert designed Q-matrix is not without issues. For example, domain experts might neglect some attributes or have different opinions about the inclusion of some entries in the Q-matrix. It is therefore of practical importance to develop an automated method to estimate the Q-matrix. This research proposes a deterministic learning algorithm for estimating the Q-matrix. To obtain a sensible binary Q-matrix, a dichotomizing method is also devised. Results from the simulation study shows that the proposed method for estimating the Q-matrix is useful. The empirical study analyzes the ECPE data. The estimated Q-matrix is compared with the expert-designed one. All analyses in this research are carried out in R. |
| 關鍵字 | Q-matrix;DINA;RRUM;CDM |
| 語言 | en |
| ISSN | 2227-7390 |
| 期刊性質 | 國外 |
| 收錄於 | SCI Scopus |
| 產學合作 | |
| 通訊作者 | Mengta Chung |
| 審稿制度 | 是 |
| 國別 | CHE |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/121840 ) |