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dc.contributor.authorFatkhudin, Aslam
dc.contributor.authorHidayatullah, M. Fikri
dc.date.accessioned2016-10-21T08:55:07Z
dc.date.available2016-10-21T08:55:07Z
dc.date.issued2016-08-27
dc.identifier.citationAiken, Lewis R., 1994, Psychological Testing and Assessment, (Eight Edition), Boston : Allyn and Bacon. Baker F., 2001, The basics of item response theory. ERIC clearinghouse on assessment and evaluation. College Park,MD: University of Maryland. Bartram, Dave SHL Group plc, Thames Ditton, Surrey, UK dan Hambleton, Ronald K, 2001, Computer-Based Testing and the Internet, USA : University of Massachusetts at Amherst. Crocker, L. & Algina, J., 1986, Introduction to Classical and Modern Test, Theory_. New York : Holt, Rinehart and Winston, Inc. Goncalves F.B., Gamerman D., Soares T.M., 2013, Simultaneous multifactor DIF analysis and detection in Item Response Theory, Computational Statistics and Data Analysis 59, 144 – 160. Horward W., 1990, Computerized adaptive testing: A primer, Hillsdale, New Jersey: Lawerence Erwrence Erlbaum Associates. Huang Y.M., Lin Y.T., & Cheng S.C., 2009, An adaptive testing system for supporting versatile educational assessment, Journal of Computers & Education 52, 53–67. Lilley M., & Barker T., 2003, An evaluation of a computer adaptive test in a UK university context. 7th Computer assisted assessment conference, 8th and 9th July, 2003, Loughborough. Ozyurt H., Ozyurt O., Baki A., & Guven B., 2012, Integrating computerized adaptive testing into UZEWEBMAT : Implementation of individualized assessment module in an e-learning system, Journal Expert System with Application, 39, 9837 – 9847. Ozyurt H., Ozyurt O., & Baki A., 2013, Design and development of an innovative individualized adaptive and intelligent e- learning system for teaching–learning of probability unit: Details of UZWEBMAT, Journal Expert System with Application, 40, 2914 – 2940. Triantafillou E., Georgiadou E., & Economides A.A., 2008, The design and evaluation of a computerized adaptive tes on mobile devices, Journal of Computers & Education 50, 1319–1330.in_ID
dc.identifier.issn2407-9189
dc.identifier.urihttp://hdl.handle.net/11617/7732
dc.description.abstractOne of the computer-based testing is the Computerized Adaptive Test (CAT), which is a computer-based testing system where the items were given to the participants adapted to test the ability of the participants. Assessment methods are usually applied in CAT is Item Response Theory (IRT). IRT models are most commonly used today is the model 3 Parameter Logistic (3PL), which is about the discrimination, difficulty and guessing. However 3PL IRT models have not provided information more objectively test the ability of participants. The opinion of the test participants were tested items were also to be considered. In this study using CAT in combination with IRT model of 4PL. In this research, the development of CAT which uses about 4 parameters, namely the discrimination, difficulty, guessing and questionnaires. The questions used were about UAS 1 English subjects. Samples were taken from 40 students answer with the best value of the total 172 students spread across 6 classes to measure the parameter estimation problem. Further testing using CAT application 4PL IRT models compared to CAT 3PL IRT models. From research done shows that the CAT application combined with IRT models 4PL can measure the ability of the test taker shorter or faster and also opportunities participants correctly answered the test items was done tend to be better than the 3PL IRT models.in_ID
dc.language.isoidin_ID
dc.publisherSTIKES Muhammadiyah Pekajanganin_ID
dc.subjectAbilityin_ID
dc.subjectCATin_ID
dc.subjectIRTin_ID
dc.subject3PLin_ID
dc.subject4PLin_ID
dc.subjectProbabilityin_ID
dc.subjectTestin_ID
dc.titleMembandingkan IRT Model 3PL Dengan IRT Model 4PL Untuk Penilaian Menggunakan Computerized Adaptive Testin_ID
dc.typeArticlein_ID


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