BULGULAR VE YORUM
4. BÖLÜM SONUÇ VE ÖNERİLER
4.5. Öneriler
- Madde seçme yöntemlerine ait SH değerleri, BSD yetenek kestirimi kullanıldığında daha düşük sonuç vermiştir. Operasyonel BBT uygulamalarında BSD yetenek kestiriminin kullanılması önerilmektedir - BBT uygulamalarının önemli savlarından biri de kağıt kalem testlerine
kıyasla daha kısa uzunlukta testler oluşturmasıdır. Elde edilen sonuçlar değerlendirildiğinde; BBT uygulamalarında BSD yetenek kestirim yönteminin tercih edilmesi önerilmektedir.
- a-tabakalama madde seçme yöntemi, test durdurma kuralı SH0.2 olduğu koşulda sonuç vermemiştir. Bu üzerinde çalışılması gereken bir bulgudur. Farklı madde havuzu büyüklükleri ve a-parametre değerleri belirlenerek araştırmalar yapılması önerilmektedir. Ayrıca, a-tabakalama madde seçme yönteminde kullanılan tabakalama sayısının da bu değişkenlerle ilişkisi irdelenebilir.
İleride yapılacak çalışmalarla ilgili olarak
- Bu araştırmada, yetenek kestirim yöntemleri EOT ve BSD yetenek kestirim yöntemleri ile sınırlandırılmıştır. Farklı yetenek kestirim yöntemlerine yer veren araştırmalar yapılabilir.
- BBT uygulamalarının bileşenlerinden testi başlatma kuralları ve madde havuzu büyüklüğünün madde seçme yöntemleri üzerindeki etkisi araştırılabilir.
- Bu araştırmada, madde kullanım sıklığı, madde havuzu kullanımı düzeyinde incelenmiştir; madde kullanım sıklığını kontrol eden yöntemlere değinilmemiştir. İleride yapılacak araştırmalarda madde
kullanım sıklığı yöntemlerinin, madde seçme yöntemlerini nasıl etkilediği konusu ele alınabilir.
- BBT uygulamalarını ilgilendiren bir diğer konu içerik balansı(content balance)dır. İçeriğe göre ağırlıklandırılmış madde havuzunda madde seçme yöntemlerinin nasıl işlediği araştırma konusu yapılabilir.
- Bu araştırmada tek boyutlu madde tepki kuramı ele alınmıştır, çok boyutlu madde tepki kuramına dayalı araştırmalara yer verilebilir.
- Eldeki araştırma simülatif olarak yürütülmüştür, operasyonel BBT uygulamalarında elde edilen bulguların nasıl işlediği araştırılabilir.
KAYNAKÇA
Bock, R. D., Aitkin, M. (1981). Marginal Maximum Likelihood Estimation of Item Parameters. Application of an EM algorithm. Psychometrika, 46(4), pp 433-459.
Costa, D., Karino, C., Moura, F., Andrade, D. (2009). A Comparision of Three Methods of Item Selection for Computerized Adaptive Testing. 2009 GMAC Conference on Computerized Adaptive Testing, June,
Deng, H., Ansley, T., Chang, H. (2010). Stratified and Maximum Information Item Selection Procedures in Computer Adaptive Testing. Journal of Educational Measurement, Vol.47, No.2, pp 202-226.
Eggen, T. H. J. M. (1999). Item Selection in Adaptive Testing with the Squential Probability Ratio Test. Applied Psychological Measurement, Vol.23, No.3., pp 249-261.
Eggen, T.H.J.M. (2004). Contributions to the Theory and Practice of Computerized Adaptive Testing. Print Partners Ipskamp B.V., Citogroup Arnhem, NL, ISBN: 90-5834-056-2.
Hambleton, R. K., & Swaminathan, H. (1985). Item Response Theory:
Principles and Applications. Boston: Kluwer-Nijhoff Publishing.
Hambleton, R. K., Swaminathan, H., & Rogers, H. J. (1991). Fundamentals of Item Response Theory. Newbury Park, CA: Sage Publications.
Han, K. (2009). Gradual Maximum Information Ratio Approach to Item Selection in computerized Adaptive Testing. Graduate Management Admission Council Research Reports, RR-09-07, June 25, USA.
Han, K. (2010). Comparision of Non-Fisher Information Item Selection Criteria in Fixed Length Computerized Adaptive Testing. Paper presented at the Annual Meeting of the National Council on Measurement in Education, Denver.
Han, K. (2012). SimulCAT: Windows Application That Simulates Computerized Adaptive Test Administration. Applied Psychological Measurement, 36.
Ho, T. (2010). A Comparison of Item Selection Procedures Using Different Ability Estimation Methods in Computerized Adaptive Testing Based on Generalized Partial Credit Model. Doctoral Dissertation, Graduate School of the University of Texas at Austin.
Iseri, A. I. (2002). Assessment of Students' Mathematics Achievement Through Computer Adaptive Testing Procedures. Unpublished doctoral dissertation. Middle East Technical University, Turkey.
Kaptan, F. (1993). Yetenek Kestiriminde Adaptive (bireysellestirilmis) Test Uygulaması ile Geleneksel Kağıt-kalem Testi Uygulamasının Karşılaştırılması. Yayımlanmamış doktora tezi, Hacettepe Universitesi
Kalender, İ. (2011). Effects of Different Computerized Adaptive Testing Strategies on Recovery of Ability. Unpublished Doctoral Dissertation.
Middle East Technical University, Ankara.
Kingsbury, G. G., Zara, A. R. (1989). Procedures for Selecting Items for Computerized Adaptive Tests. Applied Measurement in Education, 2(4), pp 359-375).
Köklü, N. (1990). Klasik Test Teorisinie Göre Geliştirilen Tailored Test ile Grup Testi Arasında Bir Karşılaştırma. Yayınlanmamış doktora tezi. Hacettepe Üniversitesi, Türkiye
Linacre, J. M. (2000). Computer-Adaptive Testing: A Methodology Whose Time Has Come. MESA Memorandum.
Linda, T. (1996). A comparision of the Traditional Maximum Information Method and the Global Information Method in CAT Item Selection. Annual Meeting of the National Council on Measurement in Education, New York, April.
McBride, J.R. (1985). Computerized Adaptive Testing. Educational Leadership, October.
Orcutt, V. L. (2002). Computerized Adaptive Testing: Some Issues in Development. Annual Meeting of the Educational Research Exchange, University of North Texas, February, Denton, Texas.
Sireci, S. (2003). Computerized Adaptive Testing: An Introduction. Measuring Up: Assessment Issues for Teachers, Counselors and Administrators, 12p.,
Slater, S. C. (2001). Pretest Item Calibration Within The Computerized Adaptive Testing Environment. Unpublished Doctoral Dissertation, Graduate School of the University Massachusetts, Amherst.
Stocking, M. L. (1992). Controlling Iitem Exposure Rates in a Realistic Adaptive Testing Paradigm. (Research Report 93-2). Princeton, NJ: Educational Testing Service.
Thissen, D. & Mislevy, R. J. (2000). Testing algorithms. In H. Wainer, (Eds.).
Computerized Adaptive Testing: A primer, Mahwah, NH: Lawrence Erlbaum Associates, Inc, pp. 101-133.
Tian J., Miao, D; Zhu, X; Gong, J. (2007). An Introduction to the Adaptive Testing, US-China Education Review, Volume 4, No.1, ISBN:1548-6613, USA.
Urry, V. W. (1977). Tailored Testing: A Successful Application of Latent Trait Theory. Journal of Educational Measurement, Vol.14, No.2, pp 181-196.
Van Der Linden, W.J., Glas, C.A.W. (2010). Elements of Adaptive Testing, Statistics for Social and Behaviorel Sciences, Springer New York Dordrecht Heidelberg London, ISBN: 978-0-387-85459-5.
Veerkamp, W.J.J., Berger, M.P.F. (1997). Some New Item Selection Criteria for Adaptive Testing. Journal of Educational and Behavioral Statistics, Vol.22, No.2, pp 203-226.
Veldkamp, B.P. (2012). Ensurind The Future of Computerized Adaptive Testing.
In Theo, J.H.M; Veldkamp, B.P. (ed). Psychometrics in Practice at RCEC. University of Twente, Netherlands, 978-90-365-3374-4.
Wainer, H., Dorans, N., Flaughter,. R., Green, B., Mislevy, R., Steinberg, L., Thissen, D. (1990) Computerized adaptive testing: A primer. Hillsdale.
NJ: Lawrence Erlbaum Associates.
Wang, T., Vispoel, W. (1998). Properties of Ability Estimation Methods in Computerized Adaptive Testing. Journal of Educational Measurement, Vol.35, No.2, pp 109-135.
Weiss, David J. (1983). Latent Trait Theory and Adaptive Testing. In David J.
Weiss (ed.). New Horizons in Testing: Latent Trait Test Theory and Computerized Adaptive Testing. (pp. 5-7). New York: Academic Press.
Weiss, D.J., Kang, G.K. (2007). Comparison of Computerized Adaptive Testing and Classical Methods for Measuring Individual Change. Graduate Management Admission Council, Item Calibration and Special Applications Paper Session, June 7.
Weiss, D. J., Kingsbury, G. G. (1984). Application of Computerized Adaptive Testing to Educational Problems. Journal of Educational Measurement, 21, 361-375.
Weiss, D. J. (2010). CAT Central: A Global Resource for Computerized Adaptive Testing Research and Applications [Online].
http://www.psych.umn.edu/psylabs/CATCentral. Last visited on 25/11/2012.
Weissman, A. (2003). Assessing the Efficiency of Item Selection in Computerized Adaptive Testing. Paper presented at the Annual Meeting of the American Educational Research Association, April, Chicago.
Wen, H., Chang, H., Hau, K. (2001). Adaption of a-stratified Method in Variable Length Computerized Adaptive Testing. American Educational Research Association Annual Meeting, Seattle.
Yi, Q., Chang, H. (2003). a-Stratified CAT Design With Content Blocking. British Journal of Mathematical and Statistical Psychology, vol. 56, pp 359–378.
EKLER
Ek:1 Araştırmanın Yürütüldüğü Grup Dağılım Grafiği
Ek:2 SimulCAT Bilgisayar Programı
Ek:3 Madde Havuzu Parametre Değerleri
Madde No a b c
1 1.138 -0.873 0.138
2 1.487 1.254 0.071
3 1.345 2.458 0.079
4 1.251 0.325 0.116
5 1.183 0.917 0.126
6 1.430 -1.694 0.096
7 1.154 -0.332 0.142
8 1.127 1.838 0.134
9 0.939 2.422 0.146
10 1.422 2.252 0.081
11 1.411 1.217 0.139
12 1.432 2.564 0.099
13 1.363 -0.583 0.092
14 1.237 -0.422 0.093
15 1.386 -0.900 0.088
16 0.925 1.555 0.055
17 0.929 -0.458 0.061
18 1.291 1.362 0.054
19 1.330 0.969 0.080
20 1.399 0.563 0.102
21 1.196 -2.730 0.054
22 0.992 1.366 0.069
23 1.477 2.860 0.056
24 1.214 -1.115 0.130
25 1.351 -1.623 0.113
26 1.464 1.633 0.073
27 1.227 -0.593 0.092
28 0.912 1.707 0.087
29 1.326 -2.088 0.078
30 1.443 -2.422 0.116
31 1.298 1.564 0.130
32 1.299 -0.053 0.063
33 0.888 1.662 0.069
34 1.052 0.584 0.054
35 1.155 1.820 0.117
36 1.010 -0.399 0.110
37 1.008 1.124 0.096
38 0.852 2.093 0.086
39 0.817 0.922 0.074
40 1.241 -1.418 0.076
41 1.205 -2.028 0.088
42 1.060 -0.798 0.096
43 1.437 0.091 0.098
44 0.863 1.068 0.074
45 1.259 0.029 0.054
46 0.951 -2.243 0.137
47 1.153 0.739 0.074
48 0.806 -2.654 0.064
49 1.006 0.729 0.065
50 1.233 -1.056 0.129
51 0.921 -0.307 0.130
52 0.920 -0.849 0.075
53 1.006 2.095 0.061
54 0.989 -0.615 0.085
55 1.420 -2.090 0.097
56 1.212 -1.485 0.139
57 1.280 -2.802 0.086
58 1.109 -1.267 0.067
59 0.829 -1.303 0.111
60 1.158 0.109 0.056
61 0.936 2.134 0.142
62 0.881 2.762 0.056
63 1.183 1.428 0.131
64 1.285 1.086 0.085
65 1.452 -0.513 0.075
66 1.070 -2.036 0.058
67 0.905 2.766 0.088
68 1.436 2.423 0.056
69 1.049 -2.699 0.083
70 0.860 -0.359 0.130
71 0.805 -0.622 0.147
72 1.304 -2.229 0.108
73 1.131 -0.452 0.146
74 1.287 -0.501 0.131
75 1.167 -1.843 0.111
76 1.142 -0.209 0.057
77 1.004 2.095 0.087
78 1.126 -1.257 0.098
79 1.097 -2.062 0.138
80 1.252 2.003 0.081
81 1.165 2.176 0.051
82 1.375 0.669 0.149
83 0.857 2.719 0.083
84 0.943 2.129 0.138
85 1.172 -2.641 0.119
86 1.496 -1.241 0.108
87 0.868 0.380 0.074
88 1.169 2.934 0.101
89 1.186 -1.987 0.133
90 1.442 2.274 0.057
91 0.890 2.899 0.105
92 1.037 2.574 0.123
93 0.886 -0.721 0.060
94 1.054 -2.652 0.115
95 1.477 -1.928 0.054
96 1.497 -1.566 0.131
97 1.363 2.540 0.071
98 1.036 -0.418 0.134
99 1.404 -1.267 0.132
100 0.800 -1.521 0.131
101 0.888 2.386 0.053
102 1.302 0.138 0.132
103 0.879 -2.528 0.052
104 1.335 -1.908 0.057
105 1.351 -0.915 0.136
106 0.899 -2.669 0.140
107 1.412 0.853 0.121
108 1.240 0.419 0.127
109 0.881 0.553 0.057
110 0.908 -0.275 0.080
111 0.979 -0.866 0.068
112 0.886 2.215 0.136
113 1.339 1.820 0.137
114 1.214 0.727 0.069
115 1.248 -2.514 0.079
116 1.141 -0.815 0.070
117 1.281 1.999 0.093
118 0.959 2.676 0.139
119 0.981 0.707 0.079
120 1.106 -1.171 0.144
121 1.004 -1.242 0.070
122 1.258 0.444 0.097
123 0.820 -0.551 0.116
124 0.921 -1.212 0.066
125 1.462 2.285 0.098
126 1.107 2.523 0.096
127 1.237 -0.069 0.089
128 1.258 2.681 0.127
129 1.258 2.758 0.074
130 1.148 -0.374 0.135
131 1.363 1.158 0.091
132 0.875 1.457 0.115
133 0.811 -0.684 0.072
134 1.323 0.771 0.094
135 1.496 -2.359 0.079
136 1.358 -1.767 0.052
137 1.099 0.523 0.074
138 1.494 -1.115 0.075
139 0.880 1.617 0.068
140 0.828 -1.359 0.062
141 1.176 2.341 0.129
142 0.844 -2.109 0.086
143 1.257 0.766 0.055
144 1.128 2.668 0.057
145 1.462 -2.402 0.136
146 0.948 -0.697 0.140
147 0.801 1.429 0.061
148 1.185 -1.994 0.150
149 0.915 -1.046 0.149
150 1.325 2.322 0.083
151 0.818 1.329 0.101
152 1.045 2.888 0.098
153 1.367 -2.628 0.113
154 1.456 -0.571 0.141
155 1.429 -0.213 0.084
156 1.182 2.439 0.063
157 0.847 0.089 0.122
158 0.887 -2.525 0.102
159 0.923 -2.556 0.127
160 1.288 0.513 0.103
161 1.069 -1.920 0.099
162 0.903 -1.718 0.116
163 0.889 -2.521 0.105
164 1.332 1.043 0.085
165 1.102 1.029 0.106
166 1.470 -1.272 0.119
167 1.017 2.324 0.119
168 1.394 2.881 0.121
169 1.010 1.798 0.076
170 1.168 -1.651 0.089
171 1.081 -0.113 0.093
172 0.979 2.143 0.141
173 1.472 2.396 0.071
174 1.480 2.426 0.119
175 0.992 -0.730 0.091
176 1.302 2.051 0.071
177 1.469 -0.553 0.065
178 1.473 2.586 0.118
179 1.028 1.987 0.067
180 1.448 0.279 0.054
181 1.059 1.159 0.051
182 1.041 0.886 0.141
183 0.838 -1.318 0.132
184 1.008 1.798 0.089
185 0.810 -2.207 0.077
186 0.831 -0.582 0.140
187 1.425 -2.652 0.050
188 1.492 -2.786 0.092
189 1.425 -0.370 0.097
190 0.942 -2.608 0.137
191 0.996 -0.951 0.059
192 0.911 2.618 0.087
193 1.431 -1.558 0.061
194 1.197 1.738 0.128
195 1.493 -0.866 0.115
196 1.143 -1.074 0.118
197 1.345 2.462 0.119
198 0.891 -2.804 0.112
199 1.301 1.957 0.064
200 1.465 -1.276 0.093
201 1.019 0.848 0.056
202 0.818 1.909 0.137
203 1.425 1.100 0.136
204 1.365 0.613 0.140
205 1.354 1.656 0.146
206 1.265 -1.480 0.081
207 1.342 -2.915 0.066
208 1.429 -0.950 0.106
209 1.295 -0.694 0.139
210 0.886 -1.237 0.054
211 1.337 -1.402 0.140
212 0.901 1.693 0.062
213 1.297 -2.446 0.067
214 1.354 1.555 0.118
215 0.801 1.204 0.062
216 1.017 0.246 0.147
217 1.367 -2.043 0.077
218 0.981 0.597 0.149
219 0.918 -2.429 0.055
220 0.822 2.802 0.132
221 1.382 1.843 0.089
222 1.118 -0.540 0.103
223 1.213 1.182 0.074
224 0.848 1.683 0.106
225 0.879 1.782 0.076
226 0.827 -1.818 0.126
227 1.184 -0.441 0.060
228 1.380 2.793 0.094
229 1.125 -1.447 0.079
230 0.833 -0.637 0.074
231 1.408 -1.021 0.102
232 0.893 2.450 0.094
233 1.059 1.611 0.131
234 1.342 -2.245 0.070
235 1.320 -1.307 0.137
236 0.958 1.740 0.139
237 1.106 1.058 0.121
238 1.444 1.360 0.077
239 1.367 2.647 0.070
240 0.831 -1.646 0.091
241 0.873 1.112 0.074
242 1.483 0.021 0.101
243 1.137 2.698 0.119
244 1.315 -2.065 0.051
245 1.215 1.075 0.062
246 1.410 1.517 0.117
247 1.167 -0.666 0.082
