Open AccessThe development of computer adaptive test and item response theory with 4 parameters based the logistics model
Author(s) -
Lala Septem Riza,
Nunung Nurjanah,
Yaya Wihardi
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1280/3/032033
Subject(s) - computerized adaptive testing , item response theory , test (biology) , computer science , mathematics education , item bank , artificial intelligence , machine learning , psychology , statistics , mathematics , psychometrics , paleontology , biology
Students’ abilities can be measured by making a test whose the number and content of questions have been determined for each student. However, it is less effective because the distribution of students’ abilities is different. By using Computer Adaptive Test (CAT) and Item Response Theory (IRT), the test can be done more quickly even though each student might solve different number and content questions. Therefore, in this research we develop CAT and IRT with 4 parameters based logistics model to evaluate the students’ ability. Some experiments conducted on 27 students with 50 number of questions were analyzed and compared with Classical Test Theory (CTT). The results indicate the system can be used as an alternative tool for evaluating the students’ ability.