Weighted Penalty Model for Content Balancing in CAT

This paper presents the Weighted Penalty Model (WPM) for content balancing in computer adaptive testing. The WPM balances content properties as well as other non-statistical constraints, while simultaneously considering item information and the scarcity of items relative to content constraints, by assigning a penalty value to each eligible item in the item pool. Items with smaller penalty values are more desirable for selection. The WPM can be applied to both fixed/variable-length CAT once proper constraint codes and weights have been assigned. In this paper, applications of the WPM are presented using both empirical and simulated data. These analyses demonstrate the success of the approach in content balancing and in achieving targeted item exposure rates in the administration of CAT.

關鍵字

Computerized adaptive testing ； Psychometrics ； Content balance ； Assessment

被引用紀錄

簡國偉（2011）。直流轉換器之大訊號開關訊號流程圖模型之推導與驗證〔碩士論文，朝陽科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0078-2611201410142306

李建宏（2012）。可改善推薦系統評價預測之使用者分群方法研究〔碩士論文，國立中正大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0033-2110201613520469

Lin, C. Y. (2012). 有效率找出k個滿足最多客戶需求/喜愛產品之演算法 [doctoral dissertation, National Tsing Hua University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0016-2002201315380422

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Weighted Penalty Model for Content Balancing in CAT

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