第五章 結論與建議
第二節 建議
本節依據研究結果及未完備之處，提供後續使用演算法於組卷研究者以下幾點 建議，做後續參考。
ㄧ、本模擬研究使用 MRCMLM 架構，探討不測驗長度與組卷設計之效果，而在學 術研究上另有其它新提出的理論模式，可供後續做組卷之相關研究。
二、演化式演算法有很多種方法，本研究使用 Kalyanmoy Deb 基因演算與粒子群演 算法，未來也可以嘗試比較不同的演算法求得最佳解。
三、本實驗設計使用複本測驗與BIB設計兩種，後續研究可嘗試使用不同情境組卷；
而實驗設計為模擬研究，所使用之試題與能力值皆在理想狀態下，未來後續研 究能使用實徵資料進行探討。
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附錄一、題庫訊息矩陣
題庫A在單峰分布之訊息矩陣
能力值區塊 -2 -1 0 1 2
-2 139.477 172.965 196.960 197.701 174.493
-1 171.873 205.361 229.357 230.097 206.889
0 193.013 226.501 250.497 251.237 228.029
1 191.342 224.831 248.826 249.566 226.359
2 167.914 201.402 225.398 226.138 202.930
題庫B在單峰分布之訊息矩陣
能力值區塊 1 2 3 4 5
1 195.511 217.967 219.110 201.187 173.715
2 218.543 241.000 242.142 224.220 196.748
3 219.273 241.729 242.871 224.949 197.477
4 199.863 222.320 223.462 205.539 178.067
5 170.930 193.386 194.529 176.606 149.134
題庫C在單峰分布之訊息矩陣
能力值區塊 1 2 3 4 5
1 93.432 121.785 150.919 169.872 168.504
2 121.539 149.892 179.026 197.979 196.611
3 150.162 178.515 207.650 226.602 225.234
4 168.421 196.774 225.908 244.861 243.493
5 166.382 194.735 223.870 242.822 241.454