Computer Based Adaptive Testing

Authors(2) :-S. Viswanandhne1, G. S. NandaKumar

Assessment is a fundamental part of the learning system. Now-a-days Computer based test is normal. Adaptive testing is a type of Computer based testing that depends on the student's ability. This adaptive testing is possible with two distinct theories. Those theories are Classical Test Theory (CTT) and Item Response Theory (IRT). CTT is moderately straightforward. This theory has simple theoretical model, which make CTT to apply in numerous testing circumstances. However, IRT has got exponential development in these late decades. IRT essentially concentrates on the item level information rather than the CTT's essential concentrate on test level information. The IRT framework incorporates a gathering of models, and the applicability of every model in a specific circumstance which relies on the test items and the viability of different theoretical assumptions about the test items. For test items that are dichotomously scored, there are three IRT models, known as three-parameter, two-parameter, and one-parameter IRT models. Finally Scoring is done, based on the parameters of the item. Students who react effectively for the most difficult question gets high score when contrasted with students who react accurately for the simplest question.

Authors and Affiliations

S. Viswanandhne1
Kumaraguru College of Technology, TamilNadu, Coimbatore, India
G. S. NandaKumar
Kumaraguru College of Technology, TamilNadu, Coimbatore, India

Assessment, Adaptive Test, CTT , IRT , Parameters

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Publication Details

Published in : Volume 2 | Issue 2 | March-April 2017
Date of Publication : 2017-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 686-691
Manuscript Number : CSEIT1722206
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

S. Viswanandhne1, G. S. NandaKumar, "Computer Based Adaptive Testing", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 2, pp.686-691, March-April-2017.
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